Extensive pedigrees reveal the social organization of a Neolithic community

Social anthropology and ethnographic studies have described kinship systems and networks of contact and exchange in extant populations1–4. However, for prehistoric societies, these systems can be studied only indirectly from biological and cultural remains. Stable isotope data, sex and age at death can provide insights into the demographic structure of a burial community and identify local versus non-local childhood signatures, archaeogenetic data can reconstruct the biological relationships between individuals, which enables the reconstruction of pedigrees, and combined evidence informs on kinship practices and residence patterns in prehistoric societies. Here we report ancient DNA, strontium isotope and contextual data from more than 100 individuals from the site Gurgy ‘les Noisats’ (France), dated to the western European Neolithic around 4850–4500 bc. We find that this burial community was genetically connected by two main pedigrees, spanning seven generations, that were patrilocal and patrilineal, with evidence for female exogamy and exchange with genetically close neighbouring groups. The microdemographic structure of individuals linked and unlinked to the pedigrees reveals additional information about the social structure, living conditions and site occupation. The absence of half-siblings and the high number of adult full siblings suggest that there were stable health conditions and a supportive social network, facilitating high fertility and low mortality5. Age-structure differences and strontium isotope results by generation indicate that the site was used for just a few decades, providing new insights into shifting sedentary farming practices during the European Neolithic.

. References strong association to hunting and the "wild world" 14 . Indeed, arrowheads and adornment and tools made from bone material from wild species are commonly found in the graves. This does not correspond to an economy based on hunting practices, however, as the subsistence of the Cerny culture is clearly based on agriculture, but the 'persona/role of the hunter' is nevertheless expressed in these selected graves of the STPs 15 . 3,5,8,13,[16][17][18][19][20]  . Of these, Fleurysur-Orne is the only site that has been excavated extensively and for which genetic data is available 22 . It is unclear how representative this site was for the region, but the site of Fleury shows differences when compared to the STP from the Paris Basin. The monuments at Fleury are earthen long barrows, some measuring up to 300 m in length, making them the longest in Europe. They were built for a single individual, or rarely for two, highlighting the very specific status of the individuals buried in them. Using genetic data from these ancient individuals, a recent study on Fleury 22 showed that: (a) almost all the individuals were males (13/14), (b) the pairs of individuals buried in the same monuments/graves were father and son, and (c) that there was no close biological relationship between individuals from the different monuments. The combined data and documented father-son line of descent suggest a transmission of sociopolitical authority through males.
The graveyard Chichery 'sur les Pâtureaux' 17 contains 15 individuals in 13 graves, including adult and subadult females and males. Except for one, all of the graves belong to pits with more elaborate architecture, also not preserved, and burials in niches 23 . The pit sizes vary from 0.71m to 2.83m according to the grave type, and only two are substantially (approximately two to three times) larger than the rest: GLN221B (2.80x1.35m) and GLN237A (2.83x0.81m). The diversity in grave types suggests cultural influences from various different regions. Rigid containers made of perishable matter are similar to those found in Monéteau 'Macherin' 16 . In Gurgy, as in Monéteau, these burials in rigid containers echo those found in regions like modern-day Switzerland or the Massif Central, and are attributed to the Chamblandes phenomenon 11 . By contrast, burials in niches were common during the time of the RRBP, but those in Gurgy do not strictly follow the standard orientation of the RRBP 4 , both for the graves and for the niches 3 .
Grave goods, notably pottery and flint tools, are scarce and randomly distributed across the cemetery. The elements of adornment, which are also rare, are remarkably diverse and include shells (e.g. scallop), perforated animal teeth (e.g. beaver), and limestone beads 3 . Overall, the observed spectrum of grave goods does not allow for a clear attribution of Gurgy to a single Neolithic culture. For example, the presence of ochre in 14 burials is a characteristic feature of the western LBK, while some shells, specifically one scallop, points to the Mediterranean sphere (Supplementary table 21, Extended Data Fig. 3c). Despite being the biggest graveyard in the Paris Basin, the site Gurgy 'les Noisats' does not match the culturally encoded funerary practices known from the region at the time, and thus represents an exception with respect to the local archaeological record.

Gurgy individuals
An anthropological investigation was conducted on all of the 128 excavated individuals. Morphological age classes for adults were assigned using the morphology of the iliac sacro-pelvic surface 26 . For subadults, tooth growth and bone maturation were used 27,28 . Osteological sex was estimated for adult and young adult individuals using the pelvis bone 29,30 , and, if not available, by applying a secondary diagnosis method 31 . 66 adult and 62 subadult individuals were identified, and from these, the genetic sex of 30 males and 20 females could be assigned, leaving 23 individuals remaining undetermined (Supplementary  table 1). It should be noted here that the individual GLN270A, previously published as undetermined 32 , has been revised in this study. Indeed, this individual could be determined to be female during the excavation in the field by standard anthropological sex determination and documented as such in the field notes. However, the pelvis bones broke during sampling/further handling, and therefore this diagnosis could not be confirmed during the laboratory analysis and was kept as undetermined. We refer the original field notes for this study.
Applying archaeothanatological methods 33 , bodies were proved to have decomposed in an empty space, demonstrating the presence of a rigid container or coffin. Bodies were mainly placed in a left-side flexed position, with some exceptions (more or less flexed, lying on their back). The main orientation of the bodies is north-south (Supplementary table 21).
Since the excavation, several studies were conducted on the human remains, specifically to look for a rationale explaining the structure of the site. The variation of the internal tooth structures such as enamel thickness, tissue proportions, and the threedimensional shape of enamel-dentin junction was investigated for 20 individuals at the site level, and variations between individuals buried in graves with different types were detected 34 .
Stable isotope analysis of bone collagen (δ 13 C, δ 15 N, δ 34 S) was performed on Gurgy individuals to study diet practices and mobility 32,35,36 (Supplementary table 24). The archaeozoological record reported the consumption of predominantly cattle, but data from Gurgy, similar to other local sites, also suggest a mixed protein consumption of cattle and pig, possibly complemented with some freshwater resources 32 . A great homogeneity was found within the Gurgy individuals. However, some differences between males and females were identified both for diet 35 and mobility 36 .
Previous aDNA analyses reported mitochondrial haplotypes from 55 individuals (based on sequences of the hypervariable region 1), which showed a variability matching the expectations for Neolithic periods in western Europe, and suggested a connection with the Mediterranean sphere 37,38 . The analysis of genome-wide data confirmed the genetic homogeneity of prehistoric individuals from western Europe during the Middle Neolithic, and provided evidence for admixture with local hunter-gatherers 39 .
An integrative study combining the mitochondrial results with archaeological data was also performed in order to understand the organisation of the site and to test whether any archaeological feature (grave goods, grave type, body orientation, etc.) could be linked to specific maternal lineages 40 . This work showed that no correlation was observed between mitochondrial lineages and archaeological data, and hence is not helping to understand the structure of the graveyard.
Additionally, on the basis of positive indication of a Hepatitis B virus (HBV) infection, two individuals (GLN201 and GLN258) formed part of a larger survey study focusing on the evolutionary history of HBV 41 . Given the nature of the horizontal and vertical transmission mechanisms of HBV, it is of interest to note that only two positive cases were detected among the studied individuals. Since both individuals were subadults, it is reasonable to expect that we would also identify the infection in their biological mothers. However, we found no evidence of transmission in the case of the pair GLN258/GLN249, while the mother of GLN201 was not found among the studied individuals.

READ
We assessed the degree of genetic relatedness using autosomal data from the complete dataset of 94 individuals by applying different approaches. We used the software READ 42 that calculates and averages the mismatch rate, denoted p0, for non-overlapping windows of 1M base pairs (bp) across the whole genome on pseudo-haploid genotype calls with randomly called SNP sites on the 1240k set (Supplementary table 8). The median value of p0 for pairs was estimated to be 0.242, which is interpreted as the expected pairwise mismatch rate for two unrelated individuals. Outliers with lower mismatch rates, i.e., lower values of p0, indicate more closely genetically related individuals, where the lowest values are expected for 1 st -degree relatives (given that there are no monozygotic twins among the studied individuals. When correcting for the median expected mismatch rate for unrelated individuals, thresholds for degrees of relatedness are calculated by READ and are set to 0.151 between identical libraries and 1 st -degree related individuals, 0.196 between 1 st -degree and 2 nd -degree related individuals and 0.219 between 2 nd -degree and unrelated individuals (Supplementary table 8). READ also provides standard errors to allow for uncertainty caused by poorer-coverage individuals. lcMLkin In order to confirm the findings from READ, we used the software lcMLkin, which estimates the probability of identity-by-descent (IBD) from genotype likelihoods 43 . lcMLkin aims to estimate the coefficient of relatedness r, the proportion of the genome common to two individuals due to direct kinship. For example, r equals 1⁄2 in the case of parent-offspring or siblings, 1/4 for 2 nd -degree related individuals, in non-inbred pedigrees. lcMlkin estimates r by estimating three parameters: k0, k1 and k2. These probabilities measure the relatedness between individuals, as they represent, respectively, the probability that none, one or two alleles, are shared via IBD between the pair of individuals. Note that k0 + k1 + k2 = 1, and that r = k1/2 + k2. While r = 1/2 for both of the 1 st -degree relationships between parent/child and full siblings, the probabilities k0, k1 and k2 differ, and are (1/4,1/2,1/4) for full siblings, and (0,1,0) for parent/child 44 . Inspection of the estimated values for k0, k1 and k2 then allows us to distinguish between both categories of 1 st -degree relationships. As the method is applied to genotype likelihoods, low-coverage data can give unreliable results, and so we therefore restricted to pairs that share at least 10,000 SNPs. We also set the thinning parameter to 10,000 to thin SNPs so that they are at least 10,000 sites apart. Results are shown in Supplementary table 9 and the coefficient of relatedness r and the probability k0 are plotted in Extended Data Fig. 1a. The Extended Data Fig. 1a allows us to visualize the two clusters of parents-offspring and siblings amongst 1 st -degree related individuals.

PMR-window approach
To investigate the spatial distribution of the PMR for 1 st -degree relatives, and how these might differ for parent-child and sibling relationships, we plotted the PMR along the genome in windows of width 1 Megabase. As stated above, the probabilities of sharing 0, 1 or 2 alleles is different for full-siblings and parent-child relationships, (1/4,1/2,1/4) and (0,1,0) respectively. Hence it should be visible that the windowed estimate of PMR for parent-child relationships is stable around the average PMR, whereas the windowed estimate for full-siblings should be more variable. Thus, to differentiate between parent-child and full-sibling 1 st -degree relationships, we visually compare the windowed estimate of PMR to the chromosomal average and the genome-wide average (Extended Data Fig. 1c). However, when one, or both, of the samples are low-coverage, it can be difficult to differentiate between variability in the windowed estimate of the PMR due to coverage, or due to a difference in the nature of the 1 st -degree relationship.

Binomial-PMR approach
In the case of ambiguous results given by lcMLkin and READ, we developed a new approach called BREADR (v. 1.0.1) 45 to estimating the PMR for a pair of individuals based on an assumption of a binomial distribution for the PMR, for pseudo-haploid data, available at https://github.com/jonotuke/BREADR. Here, for individuals i and j, we thinned the data such that all sites were at least 200K bases apart to best satisfy the assumption of independence. We did so by taking all of the overlapping sites, and their relative positions. We started with chromosome 1, where we took the first overlapping site, retained it, then took the next site that was a minimum of 200K sites along the chromosome, and retained it, etc. We repeat this until we had no overlapping sites left. We then repeat this "per chromosome" process for chromosomes 2 through to 22. In this way we found a likely optimally large set of thinned, overlapping SNPs.
We then calculated the number of mismatching base calls, denoted !,# , out of the possible !,# overlapping sites. We then calculated the "thinned" PMR, !,# = !,# !,# ⁄ . Using the logic of READ, we calculate the median PMR, denoted ^$, and define the expected PMR for a k-degree related pair as ^% = '1 − 1 2 ⁄ %&' +^$, for = 0,1,2. We then find the likelihood of the observed PMR for each value of k using the probability density function of a binomial distribution, denoted Note that we define two individuals as "unrelated" if they are more distantly than 2 nd -degree related, i.e. 3 rd -degree or more.
where -( ) is the 3-truncated Poisson distribution of the form

#+/
, chosen with = 10 as it represents well the un-likelihood of individuals always being closely related once they are more than second-degree related, but also captures the diminishing probabilities of being too distantly-related due to the finite size of populations.
We can then calculate the posterior probability of the individuals i and j sharing a k degree relationship as for which the denominator is equal to one by construction. We note that a formulation of the posterior probabilities with P(K=k) = ¼ inherently assumes that all degrees of relatedness are equally likely, but it is not clear what these probabilities should be, and so we used this uninformative prior. All cases involving 1 st , 2 nd and problematic 2 nd -degree/unrelated relationships are plotted individually and provided at https://doi.org/10.5281/zenodo.7224898.

Tree reconstruction
To reconstruct the pedigree trees, we started by reconstructing small families linked only by 1 st -degree relatedness according to the results of READ and lcMLkin (Supplementary tables 8 and 9). We combined these with maternal and paternal lineages to restrict the possible topologies to consistent trees, and with the age-at-death of the individuals to rule out impossible parent-offspring relationships (i.e., a young subadult individual cannot be a parent). With this first step we were able to reconstruct 17 small family trees, consisting of between 2 and 17 individuals.
We then used the 2 nd -degree relationships inferred by READ (Supplementary table 8) to connect together these different small family trees together. Note that 2 nd -degree related individuals could be grandparents/grandchildren, half-siblings or uncle-aunt/nephew-niece. Consistencies between these small family trees allowed us to double-check every connection.
We then applied the PMR-window and the binomial-PMR approaches to clarify potentially inconsistent results.

Reconstruction of pedigrees involving 1 st -degree related individuals
• GLN206 and GLN208 are two children 1 st -degree related as siblings (Supplementary  tables 8 • GLN225 and GLN226 are two individuals who are 1 st -degree related as parent-offspring. Given the young age of GLN226 (1-3 years old) and the shared mitochondrial haplogroup, they must be mother and son (Supplementary tables 8  • GLN287 and GLN310B are two adult males, 1 st -degree related as siblings (Supplementary tables 8  • GLN289B and GLN288 are two female adults, 1 st -degree related (Supplementary table 8, Figure Supplementary Note 2. VI). At this stage, the low coverage of GLN289B does not allow to specify if they are siblings or mother-daughter.
• GLN299 and GLN302 are father and son, but as both are male adults, we cannot determine who is the father and who is the son (Supplementary tables 8  • GLN207A and GLN279 have a READ p0 value at the threshold between 1 st and 2 nd degree, but lcMLkin results clearly show a 1 st -degree sibling relationship (Supplementary tables 8  • GLN285B is a male child who shares a 1 st -degree relationship with GLN285A and GLN248 who are not related to each other (Supplementary tables 8 and 9). The connection given by lcMLkin for GLN285B with GLN285A is the only inconsistent one (red dot within the blue cluster on Extended Data Fig. 1a). Given the PMR-window plot (Extended Data Fig. 1c) and the absence of 2 nd -degree relationships between GLN285B and both GLN245B and GLN261 (see below), GLN285B cannot be sibling with GLN285A. Hence, GLN285A and GLN248 are the parents of GLN285B (Figure Supplementary Note 2. XII).
• GLN269 has a parent-offspring relationship with GLN267, GLN227 and GLN268A who are all siblings (Supplementary tables 8 and 9). GLN269 must be their mother ( Figure  Supplementary Note 2. XIII).
• GLN305 and GLN298 have a parent-offspring relationship with GLN280, GLN291 and GLN300, and are not related to each other. GLN280, GLN291 and GLN300 are siblings. GLN307 and GLN277 are siblings, and both 1 st -degree related to GLN300 in a parentoffspring relationship. Their 2 nd -degree relationship with GLN305 and GLN298, and with GLN280 and GLN291, clearly make them the offspring of GLN300 (Supplementary tables 8  • GLN256 and GLN261 are two adult males who are 1 st -degree related as siblings. GLN250 is 1 st -degree related to GLN256 with a parent-offspring relationship, and as he shares a 2 nd -degree relationship with GLN261, he can only be the son of GLN256 and the nephew of GLN261. Similarly, GLN245B is 1 st -degree related to GLN261 but shares a 2 nd -degree relationship with GLN256 and is therefore the son of GLN261 and nephew of GLN256. GLN245B and GLN249 are not related, and they have a parent-offspring relationship with GLN245A, GLN258 and GLN244 who are siblings, and who also have a 2 nd -degree relationship with GLN261 who must therefore be their grandfather (Supplementary tables 8  • GLN317, GLN212, GLN213, GLN255 and GLN224 all share a 1 st -degree sibling relationship. GLN317 and GLN315 are not related, and both have a parent-offspring relationship with GLN202 who is their son. GLN202 indicated a 2 nd -degree relationship with all of the siblings of his father GLN317. GLN202 shares a parent-offspring relationship with GLN201 who also shares a 2 nd -degree relationship with GLN317 and GLN315. He is therefore the son of GLN202 (Supplementary tables 8  • GLN237A has a parent-offspring relationship with GLN325, GLN265, GLN221B and GLN266, who are all siblings. GLN237A can only be their father (Supplementary tables  8  GLN325 and GLN275 are not related to each other, and they share a parent-offspring relationship with GLN216 and GLN276, who are themselves siblings. Both GLN216 and GLN276 share a 2 nd -degree relationship with the siblings of GLN325, which is expected as they are their uncles, as well as with GLN237A who is their grandfather. Their father GLN275 has a brother GLN253 who also shares an uncle-nephew relationship with both GLN216 and GLN276 (Supplementary tables 8  • GLN266 is the father of the siblings GLN268B and GLN243A, who both also share a 2 nd -degree relationship with all of the siblings of GLN266, as they are their uncles and aunt, and with GLN237A as their grandfather. However, given the low coverage of GLN268B, some 2 nd degrees are missing in the READ results. By looking at the binomial-PMR distributions, the posterior probabilities of being 2 nd degree with the siblings of GLN266 are variable (with GLN325: 7%, GLN262: 12%, GLN221B: 47%, GLN265: 88%), and it stands at 98% with the grandfather GLN237A (see binomial-PMR distribution plots). However, given the configuration of the tree and the other connections, this is the only possible scenario (Supplementary tables 8  • GLN243A is unrelated to GLN236A and both share a 1 st -degree relationship with their daughter GLN262 (Supplementary tables 8  • GLN270B, who had very low coverage, and for whom we could not assess the mitochondrial haplogroup, shares a 1 st -degree relationship with GLN237A, but we cannot determine from the genetic data if it is a sibling or parent-offspring relationship. GLN270B shares a 2 nd -degree relationship with the offspring of GLN237A, as expected if he is their grandfather, or their uncle (Supplementary tables 8 and 9, Figure  Supplementary Note 2. XVII). GLN270B also shares a 1 st -degree relationship with GLN231A, who shares a 2 nd -degree relationship with GLN237A, which is not possible if GLN237A and GLN270B were brothers (Supplementary tables 8 and 9). The only possibility is therefore that GLN270B is the father of GLN237A and GLN231A is the brother or father of GLN270B, and uncle or grandfather of GLN237A. Unfortunately, we cannot resolve the relationship between GLN270B and GLN231A on the basis of the available data (Supplementary tables 8 and 9). As the PMR-window plot suggests a sibling relationship (Extended Data Fig. 1c), we nevertheless chose to keep this reconstruction in the pedigrees. GLN231A shares a parent-offspring connection with GLN322 who is a child. He cannot be the father of GLN231A, and he shares a 2 nd -degree connection GLN270B, who can be his uncle if GLN270B is the brother of GLN231A, or his half-brother if GLN270B is the son of GLN231A (Supplementary tables 8

Connections between the nuclear families with 2 nd -degree relationships
Pedigree A • The adult male GLN320 shares a 2 nd -degree relationship with GLN231A and GLN270B (Supplementary table 8). He could be either their grandfather, their uncle, or their nephew, all through the paternal line. The absence of other related individuals does not allow us to decide between these options, and the relationship is thus shown as uncertain in Figure 1a.
• The siblings GLN215A and GLN215B share a 2 nd -degree relationship only with GLN276 (Supplementary table 8). They cannot be his half-siblings because they would also be 2 nd -degree related to GLN216, the brother of GLN276, and 1 st -degree related to one of the parents GLN275 and GLN325. They also cannot be the nieces of GLN276 because they would be 2 nd -degree related to GLN216 as nieces, but also to GLN275 and GLN325 as granddaughters. They can only be the granddaughters of GLN276, and we cannot say if it is via the paternal or maternal side, as they do not carry a Y chromosome and their mitochondrial DNA is anyway different from the one carried by GLN276 (Fig.  1a).
• The siblings GLN227, GLN267 and GLN268A share a 2 nd -degree relationship with GLN266, GLN268B and GLN243A (Supplementary table 8). The only possibility of a 2 nd -degree relationship with both a parent and an offspring is if one is the grandchild of the former and the nephew/niece of the latter. GLN227, GLN267 and GLN268A are therefore grandchildren of GLN266, and GLN243A and GLN268B are both their uncles. The relationship can only be via the missing father, as the mother GLN269 does not share a close relationship with either GLN266, GLN243A or GLN268B (Fig. 1a).
• The male individual GLN236B is 2 nd -degree related to GLN262, GLN236A and GLN243A (Supplementary table 8). The only possibility is for him to be the nephew of GLN262 and the grandson of GLN236A and GLN243A. As this individual carries a different mitochondrial haplotype than his grandmother, and the same Y-chromosome lineage as his grandfather, we can assume that the link is made through the missing father (Fig. 1a).
• Similarly, the female individual GLN214 is 2 nd -degree related to GLN262, GLN236A and GLN243A (Supplementary table 8). She can only be the niece of GLN262 and the granddaughter of GLN236A and GLN243A. As she carries a different mitochondrial haplotype than her grandmother, we can also assess that the link is made through her missing father (Fig. 1a).
• GLN223 shares a 2 nd -degree relationship with GLN202, GLN315 and GLN317 (Supplementary table 8). She can only be the niece of GLN202 and the granddaughter of GLN315 and GLN317. She does not carry the same mitochondrial haplotype as her grandmother; therefore, the link can only exist through her missing father (Fig. 1a).
• GLN210 is 2 nd -degree related to the siblings GLN212, GLN255 and GLN317 (Supplementary table 8). According to the READ results, both pairs GLN210-GLN213 and GLN210-GLN224 show values just below the established threshold (Supplementary  table 8). By checking both pairs with our binomial-PMR approach, we can confirm that they are 2 nd -degree related, with posterior probabilities of 1 and 0.99 respectively (see binomial-PMR distribution plot). The two explanations for 2 nd -degree relationships with siblings are either a half-sibling or an uncle/aunt -nephew/niece connection. If GLN210 was half-sibling with these brothers and sisters via their father, he would also be 2 nddegree related to GLN237A, GLN325, GLN265, GLN221B and GLN266, which is not the case. If it was via their mother, they would all share the same mitochondrial haplotype, which is not the case. Therefore, GLN210 can only be the nephew or the uncle of the siblings GLN212, GLN213, GLN224, GLN255 and GLN317. If he was an uncle via the paternal line, he would be expected to be 1 st -degree related to the missing father's siblings GLN221B, GLN265, GLN266 and GLN325, which is not the case. If he was an uncle via the maternal line, he would be expected to share the same mitochondrial haplotype with the missing mother's offspring GLN212, GLN213, GLN224, GLN255, GLN317, which is also not the case. Therefore, he can only be a nephew via the missing father's side, because of non-matching mitochondrial haplotypes with the uncles GLN224, GLN255, and GLN317, and the aunts GLN212 and GLN213 (Fig. 1a).
• Almost all the siblings GLN212, GLN213, GLN224, GLN255 and GLN317 share a 2 nddegree relationship with the siblings GLN325, GLN265, GLN221B and GLN266, as well as to their father GLN237A, according to READ results (Supplementary table 8). A few pairs are categorized as unrelated by READ, but the binomial-PMR distribution confirm the 2 nd degrees (GLN213 and GLN221B, 0.91; GLN255 and GLN221B ~1; GLN317 and GLN221B, 0.92; GLN317 and GLN237A, 0.99; see binomial-PMR distribution plot). The only possibility is for them to be nephews/nieces of GLN325, GLN265, GLN221B and 266 and grandchildren of GLN237A. The missing parent, offspring of GLN237A, can only be a male as the siblings GLN212, GLN213, GLN224, GLN255 and GLN317 do not carry the same mitochondrial haplotype than GLN325, GLN265, GLN221B and GLN266 (Fig. 1a).
• GLN204 shares a 2 nd -degree relationship with GLN207A and GLN282 (Supplementary  table 8). The only possibility is that he is the nephew of GLN282 and grandson of GLN207A. As he carries a different mitochondrial haplotype than his uncle, we assume a link through the missing father (Fig. 1a).
• GLN206 and GLN208 are 2 nd -degree related to GLN207A and GLN282 (Supplementary  table 8). Similar to the previous case, they must be nephew and niece of GLN282 and grandchildren of GLN207A. As they carry a different mitochondrial haplotype than their uncle, we assume a link through their missing father (Fig. 1a).
• The siblings GLN207A and GLN279 are 2 nd -degree related to the siblings GLN263 and GLN321 (Supplementary table 8). If they were half-siblings connected by their father, they would also be 2 nd -degree related to GLN237A, GLN325, GLN265, GLN221B and GLN266, which is not the case. If they were half-siblings connected by their mother, they would all share the same mitochondrial haplogroup, which is not the case. If they were uncle and aunt via the paternal line, they would be expected to be 1 st -degree related to the missing father's siblings GLN221B, GLN265, GLN266 and GLN325, which is not the case. If they were uncle and aunt via the maternal line, they would be expected to share the same mitochondrial haplotype with the missing mother's offspring GLN263 and GLN321, which is also not the case. Therefore, GLN207A and GLN279 must be the nephew and niece of the siblings GLN263 and GLN321, via a missing father as they do not share the same mitochondrial haplogroup (Fig. 1a).
According to the same rationale, he can only be their nephew, via a missing father (Fig.  1a).
• In the same way, GLN257 is 2 nd -degree related to GLN263 and GLN321 (Supplementary table 8). He can only be their nephew, via a missing father (Fig. 1a).
• The siblings GLN263 and GLN321 share a 2 nd -degree relationship with the siblings GLN325, GLN265, GLN221B and GLN266, as well as to their father GLN237A (Supplementary table 8). The only possibility is that they are the nephews of GLN325, GLN265, GLN221B and GLN266 and grandchildren of GLN237A. The missing parent, the offspring of GLN237A, can only be a male as the siblings GLN263 and GLN321 do not carry the same mitochondrial haplotype as GLN325, GLN265, GLN221B and GLN266 (Fig. 1a).
• GLN232C shares a 2 nd -degree relationship only with GLN319 (Supplementary table 8). She cannot be his half-sibling because she would be expected to also be 2 nd -degree related to GLN220, GLN241 and GLN260, brothers of GLN319. Given the young age (2-6 years old) of GLN232C, she can also not be his grandmother. She also cannot be the niece or the aunt of GLN319 because she would be expected to also be 2 nd -degree related to GLN220, GLN241 and GLN260. She can only be the granddaughter of GLN319, but we cannot distinguish between the paternal or maternal side, as she does not carry a Y chromosome and her mitochondrial haplogroup would not be transmitted by GLN319 (Fig. 1a).
• GLN226 is 2 nd -degree related to all siblings GLN220, GLN241, GLN260 and GLN319, with whom his mother GLN225 does not share any genetic relationship (Supplementary  table 8). He cannot be their half-sibling via their father because we would also share a 2 nd -degree relationship with GLN237A as an uncle and with GLN270B as a grandfather, which is not the case. He cannot be their uncle via the father because he would be expected to be 1 st -degree related to GLN237A, neither via the mother because GLN225 would therefore be 2 nd -degree related to the siblings GLN220, GLN241, GLN260 and GLN319 as their grandmother, which is not the case. Thus, GLN226 can only be the nephew of GLN220, GLN241, GLN260 and GLN319 on his father's line (Fig. 1a).
• The siblings GLN220, GLN241, GLN260 and GLN319 share a 2 nd -degree relationship with GLN237A (Supplementary table 8). Their relationships with GLN270B, who is very low coverage, is problematic as the / value from READ for each individual appears just below the threshold of the 2 nd -degree relatedness. By looking at the binomial-PMR approach, we can confirm that they are 2 nd -degree related to GLN270B with posterior probabilities 0.94, 0.98, 0.94 and 0.99 respectively (see binomial-PMR distribution plot). Hence, the siblings GLN220, GLN241, GLN260 and GLN319 must be nephews of GLN237A and grandsons of GLN270B (Fig. 1a).
• GLN285A shares a 2 nd -degree relationship with GLN245B and GLN261 (Supplementary  table 8). The only possibility is that he is the nephew of GLN245B and the grandson of GLN261, via his father as he does not carry the same mitochondrial haplotype as his uncle (Fig. 1a).
• The siblings GLN256 and GLN261 are 2 nd -degree related to GLN237A and GLN270B (Supplementary table 8). They can only be the nephews of GLN237A and the grandsons of GLN270B (Fig. 1a).

Pedigree B
• The siblings GLN301 and GLN306 share a 2 nd -degree relationship with GLN280, GLN291, GLN300, GLN298 and GLN305 (Supplementary table 8). They can only be the nieces of GLN280, GLN291 and GLN300 and the granddaughters of GLN298 and GLN305 via the father's line, because of the non-matching mitochondrial haplotypes with the grandmother GLN298 and the uncles GLN280, GLN291, GLN300 (Fig. 1a).
• GLN309 is 2 nd -degree related to GLN301 and just below the threshold of the 2 nd -degree relatedness with GLN306 according to READ (Supplementary table 8). By looking at the binomial-PMR distribution, they are 2 nd -degree related with a posterior probability of ~1 (see binomial-PMR distribution plot). GLN309 must be the nephew of GLN301 and GLN306, via his father as he does not share the same mitochondrial haplogroup with his aunts (Fig. 1a).
• In the pair mother-daughter GLN288 and GLN289B, for which we were not able to determine who was the mother and the daughter as they are both adults, the individual GLN288 shares a 2 nd -degree relationship with the individual GLN291. The READ results show a / value just below the threshold (Supplementary table 8) but the binomial-PMR distribution confirms this relationship, indicating a posterior probability of 0.83 (see binomial-PMR distribution plot). This 2 nd -degree relationship cannot represent an ascendent link through the top of the tree, as GLN288 would share other relationships with the relatives of GLN291, therefore it must be a descendant link. She cannot be the niece or half-sibling of GLN291 because she would also be 2 nd -degree related to his siblings and/or parents. She must be his granddaughter. The individual GLN289B does not share a 2 nd -degree with GLN291, so she must be the daughter of GLN288, and not her mother (Fig. 1a).

Unlinked individuals
• The remaining related pairs GLN299 and GLN302, GLN287 and GLN310B, and GLN211A and GLN211B do not share any 2 nd -degree relationship with the other individuals from the group (Fig. 1a).
• Among the individuals categorized as "Unlinked unrelated individuals", the adult females GLN207B, GLN232B, GLN242, GLN243B, GLN246, GLN284 and GLN294, the subadult females GLN313 and GLN326, and the subadult males GLN229 and GLN308 do not share any 2 nd -degree relationships with the rest of the individuals buried in the necropolis (Fig. 1a).
• However, the only adult male GLN311 categorized as "Unlinked unrelated individuals" does share a 2 nd -degree relationship with GLN270B, but none with his brother GLN231A, his son GLN237A, and neither with the 2 nd -degree related individual GLN320. GLN311 carries the Y-chromosome haplogroup H2m, different from the main lineage haplogroup G2a1a. Given that both individuals share neither the same mitochondrial haplogroup nor the same Y chromosome haplogroup, an alternative possibility is that GLN311 is a grandson on the maternal side. However, this scenario seems problematic as GLN311 is not 2 nd -degree related with GLN237A, who would be his uncle in that case. Given the uncertainty, we chose not to plot this connection in the main pedigrees (Fig. 2).

Exploration of patrilocality using READ data
To explore the patrilocal pattern with an analytical approach, we used p0 values given by READ and calculated the average of every pair for each individual with every individual from the rest of the group, as performed in Villalba-Mouco et al. 2021 46 . The mean p0 value represents the average degree of relatedness of each individual to the whole group: the lower this value is, the more related the individual to the group, overall. We calculated this value separately for adults and subadults and plotted this value for each individual in both Extended Data Fig. 7a and 7b, using the following R packages: ggplot2 (v3.3.2) 47 , tidyverse (v1.3.2) 48 , magrittr (v1.5) 49 , data.table (v1.13.0) 50 , janitor (v2.0.1) 51 . We performed a Wilcoxon test to assess if the genetic sex and age groups are significantly differently related. The test is significant for the whole group (p-value = 5.156e-06) and for the adults (p-value = 1.375e-05) but not for the subadults (p-value = 0.1067). Note that these p-values cannot be directly compared due to the varying samples sizes in each case.

Supplementary Note 3. Imputation and IBD sharing analysis Harald Ringbauer, Ainash Childebayeva, Maïté Rivollat
In order to double-check the reconstructed pedigrees, we imputed higher-coverage sequence data, and then ran Identity-by-descent (IBD) sharing analysis on imputed data.
Imputing the ancient DNA data Samples were imputed using the software GLIMPSE 52 using a default pipeline developed by the authors of the software (https://odelaneau.github.io/GLIMPSE/tutorial_b38.html). We set the threshold for imputation with GLIMPSE at 500,000 SNPs covered on the 1240k panel (n=72) 53 . First, .bam files with 2 base pairs trimmed from each end of every read to account for aDNA degradation were processed with bcftools to determine genotype likelihoods using the 1000G panel 54 as a reference. Imputation was then run with GLIMPSE_impute on genomic chunks of 2,000,000 base pairs with the buffer size of 200,000 base pairs. The chunks were then ligated using GLIMPSE_ligate, and fully phased haplotypes were determined using GLIMPSE_sample.

Inferring IBD sharing
The output of the imputation of GLIMPSE was analyzed using the software ancIBD 55 (version 0.2a, https://pypi.org/project/ancIBD/). Using he recommended settings of the Python software package (v 2.7.18), we inferred IBD segments at least 8 cM long between all Gurgy individuals with >500,000 of the 1240k SNPs covered at least once (n=72). For each pair of individuals with at least one detected block of IBD (n=2412 pairs), we recorded summary statistics of the IBD sharing and report both number and total length of IBD>8, 12, 16 and 20 cM, as well as longest IBD block (Supplementary table 10).

Comparing IBD sharing with inferred pedigrees
To evaluate the concordance of IBD sharing and the inferred pedigree, we created an automatic tree crawler that reports the degree of relatedness for a given pair of individuals (implementation available at https://github.com/hringbauer/ibd_gurgy/blob/main/notebooks/tree/read_tree.ipynb). The program takes as input a table of all individuals with both their parents and constructs a directed graph, where each individual points towards its two parent individuals. The software then runs a modified Breadth-first search algorithm. First, for individual one at each ancestral node (corresponding to one individual) the degree of separation from the target sample is stored. Running the Breadth-first algorithm from the second individual, we then identify the first common ancestor. If no common ancestor exists, the algorithm returns relatedness 0. Combining the distance of individual 1 and individual 2 to the common ancestor, we obtain the degree of relatedness. Additionally, we store whether one individual is directly ancestral to the other (equivalent to the distance of one individual to the common ancestor being 0). Moreover, we store half-sibling relationships: The algorithm checks when the first common ancestor is found, and also if this ancestor's partner is a common ancestor of the same depth.
We then compared the inferred pedigree relatedness (reconstructed without IBD) with inferred IBD sharing between all 2556 pairs of 72 individuals with sufficient coverage. The results are given in Supplementary table 10 and plotted in the Extended Data Fig. 1b and at https://doi.org/10.5281/zenodo.7224898. In particular, we looked at IBD sharing for all pairs of a given degree of relatedness (1 st -8 th degree). We further grouped relatives as being ancestral to each other or being related via two shared parents (i.e., via full siblings), as IBD sharing is expected to be different because the number of meioses differ.
Considering the 1 st -, 2 nd -and 3 rd -degree related pairs, the IBD sharing analysis matches perfectly with previous reconstructed biological relatedness found via the output of READ and lcMLkin (Supplementary Note 2), confirming both the reliability of IBD sharing method as well as the robustness of our reconstructed pedigrees. The IBD analysis also confirms the parent-offspring relationship between GLN285A and GLN285B, which lcMLkin determined as siblings, but which was clearly inconsistent with both the tree reconstruction and the PMR-window analysis (Supplementary Note 2, Extended data Fig. 1a and 1b).
We note that beyond the 3 rd degree, overlaps between IBD clusters start to appear, and it is no longer possible to assign a single degree relative IBD cluster anymore (Extended Data Fig. 1b). This is expected given the biological variation of IBD sharing (and consequently all genetic relatedness). However, we can still detect definite recent genealogical links as multiple long IBD are distinctly shared for most individuals up to six degrees apart.

Pedigree A
Within Pedigree A, one pair yielded a strong inconsistency between its relatedness in the pedigree and the IBD sharing results: GLN202 and GLN243A, represented by the light blue dot on the upper end of the 3 rd -degree cluster on Extended Data Fig. 1b (Supplementary  table 10). This had been identified already via READ and the binomial-PMR method where they appear 2 nd -degree related (see binomial-PMR distribution plot), while they are only 4 thdegree related along the paternal line from the pedigree. IBD analysis further shows that GLN202's mother, GLN315, shares a 3 rd -degree relationship with GLN243A. The only explanation would be an extra connection via GLN243A's unsampled mother, such as GLN315 being the niece of GLN243A's mother. However, GLN202 and GLN268, brother of GLN243A, were found to be unrelated via READ. This might be explained by the poor coverage of GLN268. If we look at further relatedness, GLN202 and his son GLN201 show some more connections with individuals related in a descendant line with GLN243A: his daughter GLN262, his grandchildren GLN214 and GLN236B, and his nephew GLN268A (see IBD plots), indicating extra-connections between these two branches that we are not able to identify given the missing individuals in our data.
If we inspect each cluster separately for every degree of relatedness, determined according to the pedigrees (https://doi.org/10.5281/zenodo.7224898), we detect several inconsistencies in the clusters of expected 7 th and 8 th degrees of relatedness, where the pairs are more closely related than expected according to the pedigrees. These pairs represent two different groups of individuals (Supplementary table 10).
• The pair GLN232C and GLN285A should be related at the 7 th -degree but are clearly not within the cluster. Given their distant position in the Pedigree A along the paternal line, the only way to explain a closer connection would be along their maternal line, which is unverifiable as both their mothers are missing (see IBD plots at https://doi.org/10.5281/zenodo.7224898).
• The other pairs of individuals found outside of the clusters of 7 th and 8 th degrees relationships are all connected to each other: GLN206 and GLN208 in one hand, GLN256, GLN261, GLN250, GLN245B on the other hand. Both groups are more related to each other than expected from the reconstructed pedigree. Given the overall consistency of the pedigree, we propose once again a connection via the maternal line, more likely via the missing mother of GLN256 and GLN261, or a missing sister related to these individuals, as the pair GLN206 and GLN208 are consistently more closely related to the siblings GLN256 and GLN261 than to the cousins GLN250 and GLN245B (see IBD plots at https://doi.org/10.5281/zenodo.7224898).

Pedigree B
All links established in Pedigree B are consistent with the inferred IBD sharing. Both links between the mother-daughter pair GLN288 and GLN289B with GLN291 are confirmed. Moreover, the direct line between GLN291 and GLN288 is further evidenced by the IBD analysis (Supplementary table 10). This is confirmed by a 3 rd /4 th degree shared between GLN288 and both GLN298, mother of GLN291, and GLN280, brother of GLN291, who are respectively her great-grandmother and grand-uncle. The coverage of GLN289B does not allow for this individual to be included in the IBD sharing analysis.

Additional connections
The IBD sharing analysis also allowed us to identify extra-connections with previously unlinked individuals that we could not detect with the other methods READ and lcMLkin, which are limited in their resolution to identifying 1 st and 2 nd degrees.
• The most interesting link revealed by the IBD sharing analysis is a 3 rd or 4 th degree in indirect line between GLN298, mother of Pedigree B, with GLN263, an adult male of the fourth generation in Pedigree A. By looking at the individuals linked to both of these individuals, we can confirm this link with a 4 th /5 th degree between GLN298 and GLN321, the brother of GLN263, as well as between GLN263 and both GLN291 GLN280, the sons of GLN298. The exact relationship is not trivial to assess, especially as we do not know exactly how many degrees connect both individuals, but this IBD signal definitely links the two main pedigrees through a genealogical connection within a few generations (Supplementary table 10, Fig. 2).
• The siblings GLN211A and GLN211B, previously unlinked to the two main pedigrees, show a 4 th /5 th degree relatedness with the siblings GLN325, GLN265, GLN221B and GLN266. However, given the genetic distance between the individuals, and both the existence of missing individuals, and the low coverage for some present individuals, it remains impossible to establish the exact relationship (Supplementary table 10, Fig. 2).
• For two of the adult male individuals, assessed as unlinked to the main pedigrees, GLN320 was found to be as 2 nd -degree related to GLN231A and GLN270B according to READ. We cannot double-check these connections with the IBD sharing analysis given the low coverage of GLN231A and GLN270B. However, results of the IBD analysis indicate at least a 4 th /5 th -degree connection of GLN320 with the siblings GLN256 and GLN261, as well as with the siblings GLN325, GLN265 and GLN221B. This all appears to be consistent with the previous hypothesis (Supplementary Note 2) that GLN320 could be the grandfather, uncle, or nephew, all through the paternal line, of GLN231A and GLN270B (Fig. 1, Supplementary table 10).
• IBD sharing analysis confirmed the absence of biological relatedness between the two unrelated subadult males GLN229 and GLN308 and any other individuals buried in the site (Supplementary table 10). We can exclude up to 6 th -degree relatedness, as those would most likely have at least multiple long IBD segments.
• Similarly, for the adult females unlinked to the pedigree, IBD sharing analysis confirmed very distant or non-existing links between them or with any individual from the group (Supplementary table 10, Extended Data Fig. 4).
• The individual GLN326, a 2-5-year-old girl, shows numerous connections with individuals from Pedigree A, in different parts of the tree, making it difficult to disentangle. She shares some 3 rd /4 th /5 th -degree connections with the siblings GLN220, GLN241, GLN260 and GLN319, with the siblings GLN325, GLN265, GLN221B and GLN266 with whom she shares the same mitochondrial haplotype, with the nuclear family of the external paternal line of GLN275, as well as with GLN315, GLN202 and GLN201 (Supplementary table 10). On the basis of the available data, it not possible to establish the exact position for this individual, as multiple relationships are plausible.

Supplementary Note 4. Runs of Homozygosity Harald Ringbauer
We inferred runs of homozygosity (ROH) using the software hapROH (v0.60) 56 . Applying default parameter settings and using the default 1000 Genome haplotypes as a reference panel, we screened all individuals with more than 300,000 SNPs covered on the 1240k capture assay (n=86). For each individual, we report summary statistics for ROH: both the number and total sum of ROH longer than 4, 8, 12, and 20 cM, as well as the maximum ROH length (Supplementary table 11, Extended Data Fig. 9c).

Consanguinity
None of the individuals have long ROH blocks with a total length of 50 cM or more (>20 cM), which was the threshold to identify plausible offspring of first cousins 56 . The individual GLN282 stands out, as it has the most ROH and is the only individual with two ROH longer than 20 cM (Supplementary table 11, Extended Data Fig. 9c). However, both are 20-22 cM long, indicating that this individual is more plausibly the offspring of 2 nd or 3 rd cousins. We conclude that there is an overall absence of close-kin unions (defined as first cousins or more closely related) in the sample, as not a single individual yielded ROH typical of such unions.

Estimating population size from inferred ROH segments
We estimated effective population size (denoted Ne) of the Gurgy sample based on the inferred ROH, which can be interpreted as the effective size of the recent ancestry pool. For this analysis we used the function "MLE_ROH_Ne" of hapROH, and ran it with the recommended settings. Using all segments of length 4-20 cM, we arrived at an overall estimate of Ne=1834.6 (95% CI 1631-2077;  We note that Ne estimates are typically lower than census size estimates of the ancestral populations (by a factor of 3-10-fold, due to varying offspring distributions and multiple generations living simultaneously), and that they effectively measure the pool of ancestors at various time depths (according to the ROH length) 57 .
The presence of ROH longer than 4cM in 82 out of 86 individuals with sufficient coverage for this analysis, with 41 of the individuals carrying even ROH longer than 8cM (Extended Data Fig. 9c) suggest that most pairs of parents were related to each other via coancestors within the preceding 5-30 generations 56 . This finding further supports the scenario where a group consistently brought in partners from a limited number of allies and/or a select few groups, coherent with the observed pattern of controlled female exogamy. For comparison, in many Early Neolithic populations from Central Europe most individuals have no ROH longer than 4cM 58 , which indicates larger pools of ancestors, or a pioneer phase sourced from long-distance demes, while individuals from the western part of the Mediterranean wave of Neolithic diffusion show a higher background relatedness 59 .

f-statistics, IBD sharing and heatmaps
Outgroup f3-statistics were calculated using qp3Pop from ADMIXTOOLS 60 . To investigate the group diversity, we calculated outgroup f3-statistics of the form f3(individual, individual; Mbuti.DG), obtaining a value for each pair of individuals (Supplementary table  12).
Following the method described in Supplementary Note 3, we calculated the shared IBD for all the pairs formed by the 72 individuals with a coverage >500,000 SNPs (Supplementary table 10).
Using both sets of values, we created two similarity matrices which were then used to generate heatmaps using the heatmap.2 function of the R-package gplots (v3.0.4) 61 and dyplr (v1.0.9) 48 . In order to investigate the general diversity within the group, we constructed both heatmaps based of f3-statistics (n=94) and IBD statistics (n=72) (Extended Data Fig. 4a and 4c).
To explore the diversity among adult females more specifically, we restricted the analysis to the adult females who were considered to be exogenous. We also built both types of heatmaps for females who are not descendants of the main lineage (therefore excluding GLN325, GLN212 and GLN213), and excluding all subadult females, as they all have parents within the pedigrees. However, we decided to include GLN288 as she is distantly related to the Pedigree B. 16 adult females were used for the f3-statistics distance-based heatmap (Extended Data Fig. 4b) and 12 for the IBD-based heatmap (Extended Data Fig. 4d).

Results
The heatmap constructed from the outgroup-f3-statistics mirrors the relatedness patterns (Extended Data Fig. 4a). Both main pedigrees are clearly visible, forming two distinct clusters, in which each nuclear family forms its own sub-cluster. However, f3-statistics do not have enough resolution to detect links between both pedigrees. The additional small groups of related individuals are also clearly visible along the diagonal of the matrix. Some extra links also appear between the different clusters, but f3-statistics do not allow further interpretation on these connections. Note also that the uncertainty in the estimates of the outgroup-f3-statistics is presented here, and could explain potential random links.
The IBD-based heatmap, although constructed using less individuals, by the nature of the analysis itself (Supplementary Note 3), is able to detect deeper relationships, allowing for the identification of more distant connections and the visualization of the interconnections between the different nuclear families that have been detected by the IBD sharing analysis (Extended Data Fig. 4c).
When restricting the analysis to include only the exogenous adult females, the scarcity of biological connections is striking. All of the adult females are either unrelated, or only very distantly related, to each other (Extended Data Fig. 4b and 4d), except for three pairs of individuals.
As expected, GLN298 and GLN288, visible in both f3-statistics and IBD heatmaps, have already been assigned as 3 rd -degree related, and have been discussed above (Supplementary Note 3). The two other pairs, GLN315 and GLN242, and GLN232B and GLN294, are visible only in the f3-statistics heatmap. Unfortunately, three out of these four individuals did not meet the coverage threshold allowing them to be included in the IBD sharing analysis. However, f3-statistics yield similar values for GLN315 and GLN242, and GLN232B and GLN294 when compared to GLN298 and GLN288. Assuming that these f3values are roughly corresponding to a 3 rd /4 th degree between two individuals, we propose that these two pairs are connected to each other, somewhere around the 3 rd /4 th degree (Fig. 2). Following the same rationale, the f3-values also show that the adult female GLN232B shares a link with the unlinked subadult female GLN326, likely around the 3 rd -degree, as well as with the adult male GLN302, likely around the 3 rd /4 th degree (Fig. 2). Still using the f3values, the second unlinked subadult female GLN313 shows a 3 rd or 4 th -degree connection with the siblings GLN287 and GLN 310B. We do not claim to perfectly assess a strict relationship here, but given the extremely rare connections between the adult females, we felt that these were worth mentioning. Overall, the quality rank given by HaploGrep 2 is above 95% (Supplementary table  5). For two individuals, GLN279 and GLN270B, the quality rank is below 90%. GLN279 carries the haplogroup J1c1 (76%) but has many missing polymorphisms. However, as this individual is the sister of GLN207A who also carries the haplogroup J1c1, we can confirm this haplogroup for GLN279. GLN270B has too many missing polymorphisms to characterise their haplogroup, and remains very similar to the revised Cambridge reference sequence 65 . Therefore, we did not call any haplogroup for this individual.

Supplementary Note 6. Mitochondrial haplogroup analysis
In total, 36 different mitochondrial haplogroups have been found among the Gurgy individuals (Supplementary table 5). This high diversity is expected given the strong patrilocal system practiced in the group. At each generation, new females come from another group and bring along new mitochondrial haplogroups. Those are not transmitted further than to the next generation, when the new female offspring leaves the group. According to such a system, a high mitochondrial diversity is maintained, while the Y chromosome diversity is strongly restricted, as observed in numerous patrilocal populations 69 .
Several of the assigned haplogroups are not reported in their exact form amongst modern populations in Phylotree 70 (https://www.phylotree.org), though the mitogenomes are complete and well covered. For instance, the four siblings GLN260, GLN220, GLN241 and GLN319 carry the haplogroup N1a1a1a, with a quality rank of 93.15% (Supplementary table  5). All four share the same haplotype, and the sequence haplotype can be determined precisely. However, since this haplogroup was common in Neolithic populations but very rare today, the derived branches of N1a1a are not fully resolved in phylotree and thus result in lower quality ranks. We made similar observation for K1a3*1, shared by individuals GLN211A and 211B.

Mitochondrial haplogroups for 99 individuals
The mitochondrial haplogroup of each of the 94 individuals with nuclear data was used to reconstruct and confirm the pedigrees. With the exception of GRG102/GLN270B, for who we could not assign the mitochondrial haplogroup (see above), each haplogroup call agrees with the position of the individual in the pedigrees (Extended Data Fig. 3b).
Haplogroup U5b1d1 (GLN295) and J (GLN314), in the form that we recovered, are unique amongst the individuals buried at Gurgy.
Haplogroup H1 is the most common sub-haplogroup of haplogroup H and is shared by many individuals (n=13). It is therefore not possible to discern whether the haplogroup sharing with individual GLN219 was specific or random chance.
Haplogroup H26, carried by GLN312, is also carried by GLN313, but with different private mutations (Supplementary table 5). With GLN312 being poorly covered, this partial mitogenome does not allow for a confident haplotype call.
Haplogroup H4a1a+195 in GLN292 is also carried by the sisters GLN306 and GLN301 of Pedigree B, and the subadult GLN235 of Pedigree A. A connection might exist between these individuals through their maternal line, and the spatial proximity in the northeast part of the site where the individuals from pedigree B are grouped also suggests a link between GLN292 with the two sisters GLN306 and GLN301.
Finally, haplogroup J1c1b1, carried by GLN264, is carried by two other individuals, the sisters GLN277 and GLN307 from Pedigree B. The rarity of the haplogroup in the group suggests a link between these three individuals, although the position of the grave of GLN264 is not in close proximity with the two sisters.
Gurgy mitochondrial diversity Given the extremely high number of related individuals in the group, the calculation of the mitochondrial diversity is not straightforward. Therefore, a comparison with published whole-population data, which assumes a random sample of unrelated individuals, would only be possible from exogenous females and additional lineages from unrelated individuals. Thus, if we take the number of different mitochondrial DNA (mtDNA) lineages among unrelated exogenous females and additional unrelated individuals, we observed 35 unique mitochondrial haplotypes among 57 such individuals, resulting in a proportion of 0.614. Applying the same principle to the data from Hazleton North 71 , which presents the only suitable parallel to Gurgy at the moment, results in a proportion of 0.618. In comparison, the Early Neolithic LBK cemetery Derenburg 58 which has been used for a longer period of time and for which only very few biological relationships have been described returns a proportion of 0.75. A random, chronologically dispersed, cross-regional sample of the French Neolithic meta-population 39 results in a proportion of 0.84. We are not necessarily expecting to reach such a high proportion within the perimeter of the mating network of Gurgy, but we note that the mtDNA diversity is not drastically reduced, and that we observe new mtDNA haplotypes in each generation, within in each lineage.

Methods
A tiled capture assay of sites on the Y chromosome, called YMCA 72 , was applied to all genetically determined males (n=57). We assigned Y-chromosome haplogroups following the method described in Rohrlach (Supplementary table 7).
Only two Y haplogroups from different major subclades are present at Gurgy, G2a2b2a1a2 (n=51) and H2m (n=6). Given the strong patrilocal signal and the common ancestor to almost all the individuals in the site, this pattern is not surprising. Some of the individuals carrying the G2a haplogroup are not well covered, and so the resolution of their terminal branch is limited. However, as they belong to the same male lineage, they must carry the same set of mutations. The haplogroup H2m is the only external lineage brought in the group by the union of a daughter (GLN325) of the main lineage.

Phylogeography of the Y-chromosome lineages
Both derived haplogroups G2a2b2a1a2 (G-L1266) and H2 (H-P96) (specifically H2m here as defined in Rohrlach et al 2021 65 ) are characteristic for incoming farming groups 39,53,[72][73][74] . G2a2b is commonly found among male LBK individuals from Eastern Germany and Central Europe 39,53,58,73-75 , but not elsewhere in France or in Europe during the Neolithic. This specific haplogroup is, however, only present in Gurgy. Contrastingly, H2m is exclusively found in southern European sites and, using this marker, allowed researchers to track the Neolithic route of migration of humans along the Mediterranean coast, and then northward to France and eventually to Ireland 22,72,76 . For example, H2m is found in the Cerny site Fleury-sur-Orne, in Normandy, in the same cultural area 22 . Gurgy is a clear example of the arrival of both routes of Neolithic migration in western Europe, where genetic signals from both streams meet.
Surprisingly, no Y-chromosome haplogroup inherited from the hunter-gatherers has been found in Gurgy, such as I2a1a or I2a1b, while they are predominant in other regions, like southern France or the British and Irish Isles 39,77,78 .

Method
Using an in-solution capture strategy based on modified immortalized probe sequences 79 , target immunity genes sequences were enriched via in-solution capture 80,81 . After enrichment, captured library pools were single or paired-end sequenced (Supplementary table 1 For the HLA analyses, only individuals where both chromosomes yielded unambiguous typings, or ambiguous ones that could be resolved beyond any reasonable doubt, were kept. Ninety-three out of the total 1458 raw allele calls (6.3%) were overruled in favor of runner-up alleles based on anomalous coverage patterns induced by reads mapping to alleles of multiple loci, and/or consistency with related, higher quality samples. Haplotypes were assigned based on the genetic genealogy of the analysed individuals, backed by previously reported frequencies and properties such as linkage disequilibrium (LD) [83][84][85] . Given the fact that the HLA-DP region is far away enough not to allow LD between these genes and the rest of the HLA class II genes, HLA-DPA1 and HLA-DPB1 should not be considered as part of the extended HLA haplotype, and its inclusion as part of the haplotype follows mendelian inheritance patterns found in the genealogy only. To add to the readability of the HLA data on the genealogy (Fig. 1), we reduced the whole haplotype nomenclature to a four-digit combination signaling the HLA-A, HLA-B, HLA-C and HLA-DRB1 alleles present in the haplotype (Supplementary table 14

Results
A total of 63 different HLA haplotypes (from 164 total haplotypes) could be detected, all of which yielded alleles previously reported for similar contexts (Supplementary table 14). Given the fact that the Gurgy individuals are almost all genetically related to a certain extent, it is not possible to accurately calculate allelic frequencies. Instead, we present the genetic genealogy with the haplotypes inherited through seven generations. Common alleles include those previously reported for Neolithic and Bronze Age Eurasian populations 58,86,87 , including HLA-A*02:01, HLA-A*24:02, HLA-A*31:01, HLA-B*15:01, HLA-B*27:05, HLA-DRB1*08:02 and HLA-DRB1*11:01. Apart from being able to report non-statistically inferred HLA haplotypes for Neolithic Europe, we were also able to detect two recombination events in the genealogy, one among HLA class I genes and another in the HLA class II region (Extended Data Fig. 5a). The first of these events involves individual GLN267, who carries a new maternal haplotype, arising from the recombination of the HLA-A allele from haplotype A24. 51 It is of note that both HBV-infected individuals (GNL201 and GNL258) bear alleles that have been reported to be associated with HBV persistence and infection chronicity: alleles HLA-DRB1*11 88,89 and -DRB1*13 90 are present in the HLA genotype of GNL201, while HLA-DQB1*03:01 88,89,91 is present in both individuals (homozygous in GNL258). However, HLA-DRB1*13 has been shown to have also a protective effect, making the role of this allele controversial 92 .

Supplementary Note 9. Analysis of variants associated with phenotypic traits Ainash Childebayeva, Maïté Rivollat
For each of our individuals, we investigated the genotypes of 72 SNPs associated with phenotypes of interest 53,93 , which includes the 41 SNPs from in the HIris-Plex-S tool for hair, eye and skin pigmentation developed on modern European data (https://hirisplex.erasmusmc.nl) [94][95][96][97] . We calculated the genotype likelihood using the UnifiedGenotyper module of the Genome Analysis Toolkit (GATK) v.3.5. These calculations were based on the number of reads from our bam files (phred-scale mapping quality score (MAPQ)>30 and base quality score (BASEQ)>30) for each position to determine the presence of the ancestral (non-effect) or derived (effect) alleles. The results from this analysis are provided in Supplementary tables 15 and 16.
Considering specifically the SNPs involved in pigmentation, we reconstructed the most-likely phenotypes using the HIris-Plex-S tool, using the weight of each SNP in the determination of the probabilities for phenotypic assignments. For eye color, following Walsh et al 2012 97 , we set our probability threshold at p=0.7, corresponding to a ~95% probability of correctly assigning eye colors to our samples (n=52). We found that if we lowered the threshold to p=0.5 (~90%), we could assign an eye color for an additional 13 individuals. Following Walsh et al 2014 96 , we assigned a hair color for 80 individuals. Finally, for the level of skin pigmentation, following the indications in Chaitanya et al 2018 94 , we assigned levels of pigmentation to 70 individuals. Overall, the individuals from Gurgy represent the full spectrum of variation in skin, hair and eye color pigmentation, ranging from 'Blond/Dark-Blond' to 'Black' for hair colour, including ten individuals with red hair, and from 'Very pale' to 'Dark-Black' for the skin pigmentation. The eye colors were also variable, including blue (N=23) and brown (N=42). It should be kept in mind, however, that these different pigmentation spectra are based on modern European populations and may not reflect the actual appearance of prehistoric populations, especially during the Neolithic, prior to the Bronze Age migrations.

Datasets and panels
We merged our new data with the HO panel (~600k SNPs) 60,98 with ancient data published for the ancestral populations and Mesolithic and Neolithic groups in western Eurasia. See the complete list in Rivollat et al. 2020 39 . We also merged our data with the same published ancient data to the 1240k SNP panel 53 including 300 present-day individuals from 142 populations sequenced to high coverage 99 and used this dataset, restricted to the autosomes, for subsequent genome-wide analyses. We excluded individuals with less than 10,000 covered SNPs on the HO panel.

PCA
Using the HO panel we performed a PCA using the "smartpca" software v10210 (EIGENSOFT; Extended Data Fig. 9a) 100 . We computed principal components from 777 present-day west Eurasians. To compensate for the incomplete nature of the ancient data, published ancient individuals from Mesolithic and Early and Middle Neolithic periods (before ~4000 BCE) from western Eurasia were projected using the options lsqproject: YES, and shrinkmode: YES.
In the PCA, the Gurgy individuals form a homogenous genetic cluster (Extended Data Fig. 9a). Although the Gurgy individuals form a tight cluster, the main ancestor of Pedigree A (individual GLN270B) is slightly shifted upwards on PC2, but this variation is likely explained by the fact that the coverage for this individual was much lower (Supplementary  table 1 (Supplementary table  17). Twelve individuals carried a small proportion of Goyet Q2 ancestry (from 3.6% to 9.2%). If we look at their position in the pedigrees (Supplementary table 17), a few of these individuals are isolated, but two clusters seem to show the transmission of this component from a generation to another. One transmission is visible from the father GLN237A to one son GLN265 and to two grandsons GLN216 and GLN276, although it cannot be detected in any of their parents. This raises questions about the detection of that component with the qpAdm method. One explanation would be that the proportion of Goyet Q2 component is too low in both parents to be detected in our model, but, when combined in both sons, it becomes important enough to be quantified. It could also be explained by the specific SNPs present or absent in each individual. The other transmission of Goyet Q2 ancestry is visible from the man GLN261 and his brother GLN256, as well as his son GLN245B and one of his grandsons GLN258, whose mother GLN249 also carries Goyet Q2 component. It is worth noting that the son GLN258 carries more Goyet Q2 component (8.6 ± 2.7%) than both parents (GLN245B = 4.6 ± 2.6% and GLN249 = 6.2 ± 2.6%).

DATES
We used the method DATES v.753 105 to leverage patterns of ancestry covariance to estimate the date of admixture between Anatolia_Neolithic and Loschbour (Supplementary  table 18).
We applied DATES to the entire pooled group as well as to each individual separately (Supplementary table 18). Here, we assumed an average generation time of 28 years 106 . The individual estimates are overall consistent with the group estimate (34.18 ± 1.99 generations), and the old admixture date estimate between farmers and hunter-gatherers of 34.15 ± 1.84 generations before (or about a thousand years) explains the genetic homogeneity of the group.
However, a few aberrant values are observed, and are either negative or excessively large. Some aberrations are clearly due to low-coverage samples (GLN268B, GLN270B, GLN289B, GLN311). The observed threshold is about 100,000 SNPs called on the autosomes for the SNPs on the 1240k capture assay: below this limit, DATES estimates do not seem reliable, giving values of thousands of generations. Two individuals also show aberrant values even though they are well-covered and yield an important part of huntergatherer component (GLN220 and GLN232B).
Lastly, two individuals yield very recent admixture dates (GLN287, 3.39 ± 5.59 generations and GLN310B, 4.98 ± 3.55 generations). They are the only ones that indicate a very recent admixture event. Interestingly, these individuals are brothers, and they are not connected to the main pedigrees, and have no close link to any other individual in the group. Therefore, it cannot be ruled out that their direct ancestors truly underwent a very recent admixture event, even though the proportion of Loschbour ancestry does not differ from the other Gurgy individuals (GLN287 = 14.6% and GLN310B = 14.2%). For comparison, the individual Oase 1 has between 1.6 and 6.3% of Neandertal ancestry, calculated with the length of the fragments, giving an estimation of a Neanderthal ancestor as a 4 th -, 5 th -or 6 thdegree relative 107 . It is also possible that this signal could occur if their parents carried similar proportions of Loschbour ancestry, but in very different regions. i.e., the parents both carry Loschbour ancestry from (approximately) the same historical admixture event, but it was non-overlapping.

Supplementary Note 11. Strontium isotope analysis on tooth enamel and inter/intra individual mobility assessment Léonie Rey, Gwenaëlle Goude, Vincent Balter
Material, tooth growth and age estimation Fifty-seven teeth were selected and analyzed for radiogenic strontium (Sr) isotope ratios ( 87 Sr/ 86 Sr), including 10 permanent first molars (M1) (for 4 females and 6 males) and 47 permanent second molars (M2) (for 19 females and 28 males), see details in Supplementary table 23. The selection was made on the basis of the availability of the teeth for this type of analysis (macroscopic preservation, age at death), previous evidence of collagen preservation 32,36 , and the position of the individuals in the reconstructed pedigrees.
Most of the selected teeth were the M2 as their growth period reflects a specific moment in the early life of the individual, i.e., after breastfeeding-weaning time but before periods of social changes evidenced both by funerary practices 108 and carbon and nitrogen stable isotopes 36 . When the M2 was not available, or was too worn to provide a relevant profile for analysis, the M1 was selected in order to discuss female vs. male behavior pattern in early stages of life.
The mineralization stage was determined on each tooth by using Moorrees   Then, age estimation of the crown formation is provided by using AlQahtani et al. (2010) 110 (Table Supplementary Note 27). According to this last reference, for the first molar (M1) the crown starts its growth on average at 0.5 years old (±4 months) and finishes its mineralization at around 3.5 years old (±0.5 years). For the second molar (M2), the crown starts its growth on average at 2.5 years (±0.5 years) and finishes its mineralization at around 8.5 years old (±0.5 years). More information about tooth development stages can be found at https://www.qmul.ac.uk/dentistry/atlas/.
All observations (anatomical variations, pathologies, stress indicators, wear, maturation stage) and external metrics were recorded and pictures of the teeth were taken. In addition, calculus samples, impressions of the crown and μCT-scans were computed whenever possible for further complementary studies 34,111 .

Tooth preparation and Sr isotope measurement by laser ablation MC-ICPMS analysis
The teeth were cut into two pieces with a precision saw, along the longitudinal buccolingual axis, passing through the top of the mesial cusps and perpendicular to the collar (crown root junction, or crj). The mesial part was embedded in epoxy resin and polished (granulometry P4000) to obtain a smooth surface.
In tooth enamel, rasters were processed along the enamel dentine junction (edj) to cross the Retzius' striae and the transverse striations. The profiles were drawn from the apex to the crj. A laser ablation device (ESI NWR193, Omaha) was connected to a MC-ICPMS (Neptune Thermofisher, Bremen) for the measurements of Sr isotopes (LA-MC-ICPMS). The fluence of the laser was 6J/cm 2 , a repetition rate of 20 Hz, a spot size of 100 µm, and a speed of 60 µm/s were used. The ablation cell was flushed with helium at 1L/min. Argon at 750 ml/min was added as an auxiliary gas for the MC-ICPMS, which was equipped with skimmer X and sample Jet cones. Blanks were measured during a period of about 5 seconds (laser off) before each measurement. We used a standard sample-bracketing method with sintered SRM1400 "Bone Ash" as the bracketing standard 112,113 . Strontium isotope measurements were corrected using the classical 85 Rb and 83 Kr corrections and the 87 Sr/ 86 Sr ratio of the measurement was subsequently normalized by the bracketing SRM-1400 standards with a factor depending on the position of the spot relative to the bracketing standards. Statistical analyses were performed, and graphical outputs were produced, using the data.table 50 and ggplot 47 packages, respectively, of the R software 114 (Supplementary table 23 115,122 . The range of 87 Sr/ 86 Sr values is detailed later for each regional geologic layer and shows a large variability. Plant 87 Sr/ 86 Sr values are preferentially used here, as they reflect a more relevant average of bioavailable Sr than soil values 116 . In a more recent study, Willmes et al. 117 mapped Sr isoscapes for the whole of France from geological units. While the range initially appears homogeneous across the Paris Basin on a geologic scale, closer observation moderates this apparent homogeneity. The site is located primarily in the Quaternary alluvial plain, consisting of sands and gravels ( 87 Sr/ 86 Srplant q3 = 0.70808 ± 0.00001, according to one sample F12-149 coming from another valley, the Marne valley, about 100km away). Immediately adjacent to this layer, moving away from the river, is the Lower Cretaceous c1 layer consisting of clays, sands, and sandstones ( 87 Sr/ 86 Srplant c1 = 0.71016 ± 0.00001 according to one sample F12-147 collected in the Aube valley, also located almost 100km away) 122 . Downstream and still near the sites is the Senon plateau (Upper Cretaceous layer c2, 87 Sr/ 86 Srplant c2 = 0.70890 ± 0.00140 according to 2 samples F11-121 and F12-146 collected more than 70 km from Gurgy) with chalk and chalky marls 122 . A few tens of kilometers further on, cretaceous layers, in the sedimentary plateau of the Paris Basin, are the pq1, e, and g layers, mainly composed of sands, clays, and gravels, with a slightly higher 87 Sr/ 86 Sr signature ( 87 Sr/ 86 Srplant pq1 and e =0.70869 ± 0.00002 and 0.71298 ± 0.00002 according to 2 samples respectively, F11-122 and F11-119) 122 . In some places, the m and q2 layers merge, on which the plant samples show a 87 Sr/ 86 Sr ratio around 0.714 (F11-117 = 0.71377 ± 0.00002 for m layer and F11-123 = 0.71432 ± 0.00002 for q2 layer) 122 . Upstream towards the Morvan massif, there is the plateau and the Jurassic formations of the Auxerrois with limestones ( 87 Sr/ 86 Srplant of layers j3 to j1 from 0.70833± 0.00002to 0.71464 ± 0.00001 according to 5 samples; increasing from j3 to j1). The Morvan massif with plutonic and volcanic rocks, such as granites and gneisses, has a significantly higher 87 Sr/ 86 Sr ratio ( 87 Sr/ 86 Srplant of layers 15 to 18, bk and h3 range from 0.71355 ± 0.00002 to 0.71893 ± 0.00037 according to 6 samples).
Thus, considering a 10-15 km radius around the site, which could represent the direct food supply environments, the area includes layers q3, q2, c1, c2, and j3. According to the IRHUM data compiled above, the corresponding range of bioavailable Sr isotopic ratios may be about 0.7075 to 0.7145. If only the q3 and c1 layers are considered more precisely, the local range narrows to the interval of approximately 0.7081 to 0.7102.

Quality control of the measurements
The average value of the 87 Sr/ 86 Sr ratios of the standards is 0.71325 ± 0.00062 (n=55), close to the accepted value of 0.71310 118 . The average Sr voltage, approximated by the 88 Sr voltage, was 7.2 ± 0.6 V (n=55) well above the ~0.5 V threshold where the 40 Ca-31 P-16 O polyatomic interference on mass 87 can produce unresolvable interferences [119][120][121] .
The value of the 87 Sr/ 86 Sr ratio of the standard tends to the true value (0.71310) as the 88 Sr voltage increases (Extended Data Fig. 8a). The value of the 87 Sr/ 86 Sr ratio of the samples was always lower than that of the standards (Extended Data Fig. 8b) but was always higher than 0.9 V (Extended Data Fig. 8c). All the measurements in the samples produced variations of the 87 Sr/ 86 Sr ratio as a function of the estimated dental age (Extended Data Fig. 8d).
Bulk Sr isotope ratios and relative variability with respect to the local geological range   A different picture according to generations Figure 3 shows the relationship between the 87 Sr/ 86 Sr values and the generation number, genetic sex, and residence status (local vs. non-local as defined above) for the individuals of Pedigree A, and suggests that the 87 Sr/ 86 Sr values appear to change over time. Males in the first generations had particularly low 87 Sr/ 86 Sr values, indicating that they spent their childhood in another location and arrived later in Gurgy. Moreover, each of these generations presents successively a higher 87 Sr/ 86 Sr value and non-local females for each generation present lower ratios than local individuals (males and females). To statistically test for the significance of sex, age, and generation in predicting the distance between burials, we ran a multivariate linear regression, beginning with a full interaction model including these three variables: generation, sex and age category. We used ANOVA (p-value cut-off of 0.05), and stepwise AIC (Akaike information criterion), to compare the nested models to find the simplest well-fit model. We found that the model which fits best is a model with generation and sex, as well as an interaction term between sex and generation, as predictor variables. The age group variable however could be completely removed from the model. The diagnostic plots for the models were all inspected to ensure that the assumptions of linear regression were satisfied. The coefficient of the interaction term "male:generation" was negative, meaning that per generation, the strontium ratio for females was increasing significantly faster than it was for males (p=0.01474).
The variation of the 87 Sr/ 86 Sr values observed through the generations does not reflect a specific mobility pathway as mentioned previously when considering the geological map. Hence, it is not possible to track the geographical origin of the individuals or generations. However, these data indicate that for each generation, the childhood of some of the individuals was spent in different places compared to the previous and following generation. It should be noted that the generations may be non-discrete and chronologically overlapping, depending on the age at which the women gave birth, and hence does not necessarily correspond to the same time periods. It seems that each generation did not settle in the parents' residential area, but in a new area, and the scale of the suggested territories is unknown. With 87 Sr/ 86 Sr values being sensitive to slight differences in the substratum, these territories could be a few hundred meters apart, or several kilometers. For the first time, these data attest to a "short-term" exploitation of the environment that could be defined as "intergenerational territorial mobility".
The variability of 87 Sr/ 86 Sr values recorded in the enamel of females and males testifies to a different geographical origin according to the status (local vs. non-local) or biological relatedness. Moreover, in Pedigree A, a difference is recorded between the females from the local group ("endogenous females") and the females with no genetic ancestors within the local group ("exogenous females"), whichever generation is considered (Fig. 3). This strengthens the hypothesis of the external origin of "exogenous females" coming from non-local communities. 87

Sr/ 86 Sr intra-profile variation and individual life histories
The cutting-edge methodology used here, LA-MC-ICPMS, to get high-resolution sequential 87 Sr/ 86 Sr data on enamel allows us to reconstruct a clearer picture of the lifestyle of the first farmers at Gurgy 122 . The early life mobility is clearly visible in the Gurgy individuals' childhood from the enamel 87 Sr/ 86 Sr sequences (Extended Data Fig. 8d). No recurrent individual mobility pattern can be identified according to the genetic position in the group (endogenous, exogenous, non-related), or the sex of the individual between 6 months until 8 years old, nevertheless, several individuals show clear 87 Sr/ 86 Sr variation between 4 and 6 and/or between 6 and 8 years old: GLN206, GLN221B, GLN243A, GLN250, GLN257, GLN261, GLN268B, GLN285A for endogenous males; all three exogenous males, GLN216, GLN275, GLN276; GLN325 for an endogenous female; GLN225, GLN236A, GLN248, GLN315 for exogenous females; as well as most of the individuals from the Pedigree B, and non-related individuals. The few profiles that are available for early life (first molar), i.e., between 6 months and 3 years old approximatively, also indicate 87 Sr/ 86 Sr variation during infancy, and echoes previous findings from prehistoric farmers from Mediterranean Europe 123 . However, no recurrence in the profile pattern is found, with these being variable and showing various types of movements without apparent overlapping. Some individuals show signs of mobility during the reporting period; regardless of sex, origin status or generation, the profiles indifferently increase, decrease, or vary intermittently. Several movements could be considered in terms of group mobility, whatever the group of origin, and in parallel with an exogenous genetic origin.

Supplementary Note 12. Geospatial analyses Mélie Le Roy, Maïté Rivollat, Stéphane Rottier, Adam Benjamin Rohrlach
A geospatial analysis was performed using the ArcGIS v.10.8 software 124 . Potentially statistically significant spatial associations between each specific and combined funerary/osteological variable, and each maternal haplogroup/haplotype/family attribution and the generations were investigated.
To analyse the dispersion of the burial pits inside the necropolis of Gurgy 'les Noisats', x-and y-coordinates for each individual were defined using the centre of the burial as the origin. Global characteristics of the site were defined by the centroid and an ellipse of one standard deviation was used to compare the distributions of selected grouped data. Then, ellipses of one standard deviation for each funerary, osteological variable, and the genetic data, were measured. The orientation and size of the ellipses indicated where the studied data were distributed (at one standard deviation).
Next, spatial distance analyses were used to highlight clusters within the entire necropolis area using the software CrimeStat 3.3 125 . The nearest neighbour index was measured to identify the difference of the mean distance from the expected distance compared with the mean distance for a random distribution. This index is calculated using the ratio between the two mean distances. According to the method, the distribution can be clustered, random, or dispersed 126 . In order to identify these aggregates, we used the K Ripley's and Hotspot Analysis using Nearest Neighbour Hierarchical spatial clustering 126 . These statistics allowed us to consider only the geographical coordinates of the chosen data and were used only on osteological and archaeological data. Several clusters have been identified previously 40,127 . Among these, only three spatial clusters (subadults, adults, males) include individuals sharing a common funerary trait, e.g., same position of the body or same type of pit. All other identified clusters always exhibited only one shared trait, e.g., the same position of the upper limb, the same type of pit, etc.
Following Zvelebil and Pettitt (2013) 128 we tested the combination of archaeological data with aDNA through this innovative GIS approach.

Distributions of the two families
The families appeared to have an exclusive distribution through the necropolis area. However, this is not significant when considering the deviational ellipses at 2SDE (80%), even though those at 1SDE (60%) do not overlap (Extended Data Fig. 6b). The different orientation of the ellipses, added to the visual separated distribution, suggests two distinct phases. This could represent either a chronological succession of occupations, or pedigrees A and B settling the area at the same time and voluntarily keeping two defined spaces in the necropolis.

Geospatial statistical analysis
Given the apparent familial-relationship structure of the site, we further explored the structure of these burial relationships within each pedigree area. We applied a Mantel test 129 to check for the correlation between spatial distances (Supplementary table 20) and genetic distances using observed f3-statistics (Supplementary table 12). The observed correlation was significantly positive (r = 0.2190748, p = 0.000009), implying that, overall, the closer two individuals are genetically related to each other, the spatially-closer they are buried.
We compared the spatial proximity to the type of relatedness (as inferred by the pedigree) that each pair shares when the pair involves an adult male and a close relative, adult or sub-adult, male or female, offspring or nephew/niece. We fit a linear model predicting distance between burials based on two possible predictor variables: the type of relationship in the form of to/from, i.e., father/son, and the age of the younger individual (adult/subadult). We found that a square root transformation for the distance fit best via the Box-Cox transformation 130 . We then fit a mixed effect model 131 of the form sqrt(distance) ~ relationship*age, and found that the random effect of who the older individual was not required (p=0.2147). Using analysis of variance (ANOVA), we found that an additive model fit better than the full interaction model (p=0.1544), but that this model could not be simplified further, hence the final model was: sqrt(distance) ~ relationship+age (p=9.563e-05 and p=2.442e-07 for the single term models via ANOVA). The estimated coefficient for the age of the subadult was negative, indicating that subadults are buried significantly closer to their parents, than adults are to their parents.
Performing pairwise comparisons of the coefficients for the relationships 132 , and adjusting the p-values using the false discovery rate (or FDR) method, we observed three groups that were significantly different (Fig 1e): -father_daughter -father_son -the positive coefficient here indicates that sons are buried significantly closer to their fathers than daughters are (p=0.0306).
-father_son -uncle_pat_nephew -the negative coefficient here indicates that sons are buried significantly closer to their fathers than they are to their paternal uncles (p=1.67e-6).
-father_son -uncle_pat_niece -the negative coefficient here indicates that sons are buried significantly closer to their fathers than nieces are to their paternal uncles (p=4.77e-7).
This findings are in line with previous observations where preferential association between male adults and subadults under 7 years old has already been described 40 . We could not apply this analysis to the adult females as the extremely small number of observations did not allow for robust statistical inference. Therefore, we cannot rule out the possibility of a similar pattern for the adult females.

Endogenous and exogenous females
No distinct location within the necropolis can be observed between endogenous and exogenous females. In contrast, all of the adult females with offspring tend to be spatially integrated into their partner's area, and buried closely to their offspring, with the unrelated females spread across the necropolis, which may indicate non-biological connections.
Pedigree A Within Pedigree A, no specific funerary practices were observed across the whole lineage (Supplementary table 22). No common funerary practice seems to be correlated to the age at death, nor to the sex of the individuals. However, the concentration of burials according to biological sex of the individuals is apparent in the eastern part of the necropolis, where female individuals were located/aligned on/along the outer rim of the area of the first phase of interments (generations 1 to 3).
This, then, led us to investigate potential correlations across generations or "nuclear families" (parents/offspring, siblings etc.).
Regarding the general distribution of the burials temporally along the generations of Pedigree A, we first noticed an expansion from east to west, up until the third generation. From this time, the distribution of the burial and the expansion of the overall necropolis followed a preferential orientation from north to south (Extended Data Fig. 6b).
No common funerary criteria are observed across generations, or close genetically related individuals (for example siblings or cousins) (Supplementary table 22, Extended Data  Fig. 3c). This can be affected by the fact that some of the family members died at a young age, while others grew old and started their own families, therefore acquiring a different social status within the community, which was then reflected in the funerary practices. However, no common funerary practice among nuclear families was observed either. Nevertheless, selected funerary criteria were shared by few members of some nuclear families. A nuclear family of parents (GLN245B and GLN249) and their three children (GLN245A, GLN244 and GLN258) is clustered in the west of the necropolis, and the parents share the same body position (on the left side), while the offspring all display the same body position (supine). In another example, a mother and her son (GLN225 and GLN226) display the same body position, and both had ochre in their burial. However, these observations were not systematic across the different nuclear families (Supplementary table 22, Extended Data Fig. 5a).
We also detected some similarities in the body position of fathers and sons being adults without offspring buried in the site: GLN237A and GLN221B are in the biggest graves lying down on their left side, with hyper-flexed arms and extended lower limbs. GLN275 and GLN216 are both on their left side, with hyper-flexed arms and legs.

Pedigree B
Some similar funerary practices are observed among the female individuals of Pedigree B (Supplementary table 22, Extended Data Fig. 3c). These individuals present similar decay space and grave good associations, even though this is not true for all individuals. Males do not share any common pattern across the four generations. Some degree of structure can be observed in the distribution of the burials. First generations appear on a north-east/south-west axis, while later generations are located on both sides of this axis, which seems to indicate some symmetry.

Isolated individuals
Since no clear pattern could be assigned to the different nuclear families, it is not possible to extrapolate or even suggest any link between the biologically unlinked and unrelated individuals with known families. For instance, it is expected that the seven unlinked adult females are partners of some of the adult males buried on the site, but in the absence of offspring, genomics can of course not detect these relationships. Unfortunately, the archaeological data (position, grave goods, spatial location) cannot help to propose more associations (Supplementary table 22, Extended Data Fig. 3c).

Supplementary Note 13. Bayesian modelling of radiocarbon dates Stéphane Rottier
The radiocarbon dataset Twenty-five radiocarbon dates have been previously published 37 . Eight new dates are available in this study, seven of which have been generated within the framework of the ANR/DFG-funded project INTERACT at the CEDAD -CEntro di DAtazione e Diagnostica, Salento University, Lecce, Italy (code LTL), and another, for GLN275, was generated at the CDRC -Centre de Datation par le RadioCarbone, Lyon 1 University, Lyon, France. The full range of all radiocarbon dates from Gurgy spans from 5,205 to 4,353 calibrated (cal.) BCE (according to IntCal20.14c 133 ). All the details are available in Supplementary table 1.
We note some inconsistencies between the radiocarbon date estimates and the individuals within the order of generations on the reconstructed pedigrees, taking into account the estimated age at death and the biological relationships. For example, the radiocarbon date of GLN201 in generation 5 of pedigree A ranges from 5,205 to 4,839 cal. BCE while his father's (GLN202) radiocarbon date ranges from 4,534 to 4,353 cal. BCE (95%). Even if the son died before his father, it is impossible for such a chronological gap to occur between the two. This example as well as others reported recently 134 shows that biological relatedness can be taken into account to identify potential radiocarbon dating outliers.
Bayesian radiocarbon date modelling with ChronoModel 2.0.18 The genomic data obtained for Gurgy and the reconstruction of the pedigrees required a reassessment of the radiocarbon dataset available for the site. So far, in the absence of contextual observations that would help to constrain the calibrated radiocarbon dates, the full interval spanning from 5,204 to 4,356 cal. BCE has been used (Extended Data Fig. 10a). This is not entirely incorrect, but according to the new pedigrees, some dates must be considered outliers. Shifts of several hundred years in the chronological intervals for some individuals who are only separated by a few generations at most are simply impossible 134 . Moreover, spatial management, especially the rare overlaps, and the way they are almost always superimposed on the outline of the first dig, as well as the possible marking of grave sites 23 , are all indications that already suggest a relatively short period of use for the site.
Chronological modelling based on date series, to which constraints are applied, have been extensively developed in the last few decades [134][135][136] . Using the Bayesian approach implemented in the ChronoModel software 137,138 , it is possible to largely reduce the width of the chronological interval in which the Gurgy necropolis was in use.
ChronoModel 2.0.18 is a software package that aims to model archaeological data in order to estimate a date for a single event, or sequence of events, based on individual dates from archaeological artifacts assumed to be contemporaneous. The model is based on a hierarchical Bayesian statistical approach which includes the potential outliers that might be due to different errors (laboratory and calibration curve errors, contamination, taphonomy). Individual dates can be constrained by evidence from external, contextual observations such as stratigraphical or typochronological data. ChronoModel 2.0.18 is an open-source and freely-available software (https://chronomodel.com).
To better model the radiocarbon date estimates on the study interval (set between 5500 and 3500 BCE), we initialised a total of 33 events (radiocarbon dates) into 15 phases (pedigrees/groups of individuals), with 8 total phase constraints (see Supplementary table 25 for exact details). We then ran three independent Markov chain Monte Carlo chains, from three different seed values. Using a mixing level of 0.99, for each chain we ran 1000 interations for burn-in with 20 batches, 500 iterations per batch, and a thinning parameter of 10, yielding a total of 111000 total iterations per chain. We used the default Metropolis-Hastings adaptive Gaussian Random Walk method for all events.

Relative chronology
First, it should be kept in mind that the chronological range resulting from radiocarbon dating is in a 95% confidence interval, and hence only includes 95% of the possible dates for the event being dated. The constraints that will be applied to the series of dates therefore theoretically allow us to find a new interval in which 95% of the possible dates for this event would be located. This event may be a one-off in time, or it may develop over a period of time, for which we will then speak of a phase.
The first step consists of a time constraint corresponding to the expected duration of use of the necropolis estimated by the number of generations of the bigger pedigree, which indicates a limit for the time of development of the phase in question.

Information from the pedigrees
The individual GLN270B is the common ancestor in Pedigree A. He was discovered in the only secondary burial, likely brought from another location where he was first buried, and where his body decomposed. He had at least three sons who had descendants themselves, some of whom were buried in Gurgy. Nine of the grandsons and one granddaughter reached adulthood and are also buried at the site. We can therefore hypothesize that it was this third generation which came to the site, leaving behind their siblings and ancestral relatives who had died before at a younger age.
The presence of subadults in the fourth generation corroborates this hypothesis, as they were the first subadults to die once the group had settled in Gurgy. However, the deficit of children in the fourth generation is notable (only 4 subadult individuals for 15 identified adults in addition to 14 adults who were inferred from the pedigrees but who are missing in our dataset). We suggest that the third generation came to the site with their children born elsewhere who then grew up around Gurgy. This would explain the low number of subadults buried in the site for this generation.
In the fifth generation, the ratio between the number of children buried (n=10) and the number of adults who would have been born in situ (n=9) is balanced. Nevertheless, of these adults born on site, only 5 are available on our dataset, which raises the question of whether the remaining individuals had left before their death. This echoes the exclusive presence of subadults in the sixth and seventh generations.
The second pedigree, Pedigree B, cannot help us to narrow the age estimates because it is impossible to link it to Pedigree A chronologically. However, the overall pattern is similar to Pedigree A. The last two generations are represented almost exclusively by subadults (with the exception of the adult female GLN277, descendant of the main lineage), whereas the first two are represented only by adults.
Therefore, if we use the Pedigree A, excluding the founding and migrating generations, and considering the possible gaps between generations, the duration of the site use was likely rather short, perhaps only 2-3 generations or ~56-84 years (we consider one generation to be 28 years 106 ).
Following these observations, we considered the relationships established in Pedigree A and used these as a framework for constraints (Extended Data Fig. 10b).

Information from the archaeological data
In a second step, the constraints arising from stratigraphic relationships observed in the field were applied, as well as the coherent groupings between individuals who show without doubt anteriority over others, either individually or grouped together (Extended Data Fig.  10c).
For example, the four siblings of individual GLN317, specifically GLN212, GLN213, GLN224 and GLN255, were buried to the west of GLN317. However, the mother of their sons, GLN315 was buried to the east, and GLN223, his granddaughter, was buried on top of him. The other son of GLN317, GLN202, probably died later as he was buried in another part of the necropolis, together with other branches of the Pedigree A, and possibly the most recently deceased of this family line, including GLN201. The individuals GLN243A and GLN243B, buried in the same pit on the top of each other, clearly show the anteriority of GLN243B. Given their position in the pedigree, their age-at-death and their location in the necropolis, they can also be considered anterior to GLN201 (Extended Data Fig. 10c).

Results
Taking into account the constraints given by both the pedigrees and the archaeological context, we modelled five separate scenarios with ChronoModel 2.0.18. We modelled one scenario with a 15-year interval of use to test the hypothesis at a very low threshold, another two scenarios with a 30-year and a 60-year interval, and another scenario with an 80-year interval in order to test the sustainability of the model. We also investigated a scenario with a 120-year interval to explore the volatility of the model (Extended Data Fig. 10d).
For the 15-year interval scenario, the heterogeneity of the date set does not allow for the model to be applied, placing 95% of the possible dates in a range between 4,793 and 3,915 cal. BCE. The constraint applied here is thus too narrow to be feasible.
For a proposed duration of 30 years, the model calculates a possible effective duration of 27.5 to 30 years with a settlement starting between 4,731 and 4,637 cal. BCE and an abandonment between 4,704 and 4,610 cal. BCE (Extended Data Fig. 10d). For a duration of 60 years, the model estimates that the site was settled between 4,739 and 4,649 cal. BCE and abandoned between 4,681 and 4,591 cal. BCE (Extended Data Fig. 10d). For a duration of 80 years, the model calculates that the site was settled between 4,751 and 4655 cal. BCE and would be abandoned between 4,672 and 4,576 cal. BCE (Extended Data Fig. 10d). For a duration of 120 years, the start of use of the necropolis would be estimated to be between 4,761 and 4,667 cal. BCE and places its abandonment somewhere between 4,646 and 4,552 cal. BCE (Extended Data Fig. 10d).
Finally, irrespective of which interval we consider in the Bayesian modelling, from 30 to 120 years of duration of the necropolis, the pedigrees and archaeological context allow us to constrain the radiocarbon dates to an interval covering at most four centuries, and at the least two centuries, from the mid-48 th century BCE to the mid-46 th century BCE (Extended Data Fig. 10d).  Fig. 1e), even though we observe a general trend of spatial clusters following genetically closely related individuals (Fig. 1c).

Supplementary Note 14. Interpretation of the Gurgy necropolis and inferences on the settlement
The main paternal line of Pedigree A starts with individual GLN270B. This man has a particular archaeological status as his burial is the only secondary burial of the site, located within the grave of the female GLN270A, from whom we could not obtain DNA data (Fig.  1d). Only his long bones were deposited in the pit, likely in a bundle next to the articulated skeleton of GLN270A, while the rest of the skeleton of GLN270B was missing. This suggests that these remains have been transferred and buried during the early phase of the site, probably because he represented, together with his brother GLN231A, the main ancestors of the pedigree, and potentially the senior lineage male. This leads us to hypothesize that this grave was a founding event in the history of the necropolis, even though the relation to the female GLN270A remains unclear. GLN270A could be a close relative (mother, sister, daughter, or, possibly, a further connection), or reproductive partner. Alternatively, it could also be the burial of a random person, whose grave pit was prepared and to whom the remains of GLN270B were added opportunistically. Irrespective of the explanation, the will to translocate the remains of this main ancestor to the site, even if he had potentially died a long time before the secondary burial, marks the importance of this individual and his lineage in the creation of this new burial place for, and by, his descendants. If GLN270A was indeed the partner in life of GLN270B, then it is also interesting to note that the translocated remains were buried with her and not his brother (GLN231A) or his potential uncle/half-sibling GLN320, which would further underpin the significance of this lineage, now represented through her, and thus GLN237A potentially being the first-born son.
In fact, the importance of the main paternal lineage can also be traced in the subsequent generation directly following GLN270B. The two largest graves at the site were built for his son GLN237A, the only individual of his offspring who yielded DNA data, even though he must have had at least two more sons as inferred from the pedigrees who might have been buried at the site, but for whom no DNA data were obtained, as well as his grandson GLN221B, i.e., the son of GLN237A (Fig. 1a, Extended Data Fig. 6d). We hypothesize that a form of social status was transmitted along the paternal line to his son and grandson, which is visible in some of the funerary practices.
Both genetic and archaeological data are consistent with a patrilineal structure of the group, potentially reflecting local understandings of genealogy and descent.
Patrilocality and female exogamic residential system In parallel to the patrilineal signal, we also observe evidence for the practice of patrilocality within the group. Adult females buried at the site, whether they are mothers or not, are from a different lineage than those of the main pedigrees. Six out of twenty of these individuals represent an exception to this rule (GLN325, GLN212, GLN213, GLN277, GLN288 and GLN289B; Extended Data Fig. 2b), with only two out of these six having children buried on site. We note that almost all female descendants from the main lineage who reached an adult age are missing, if we account for a natural expected ratio of 1.05:1 males/females at birth 139 , while the ratio among adult offspring at Gurgy is 4.5:1. This can in parts be explained by males staying in the group, i.e., practices of patrilocality, akin to the patrilineal structure discussed above in conjunction with a female exogamy, in which females move from their birthplace to their reproductive partner's home. Seven adult females are not connected to the pedigrees, and also not distantly related as shown by the IBD sharing analysis (Supplementary Notes 3 and 5). We thus speculate that these could be the reproductive partners of males from the main pedigrees, with whom they either did not have offspring together, or whose offspring were not buried at the site, or for whom we did not recover DNA, that would allow us to link these females to the pedigrees. This pattern of female exogamy is clearly visible in the Extended Data Fig. 7a where a significant sex difference is observed with respect to the mean relatedness coefficient at the site, meaning that adult females had on average significantly fewer relatives at the site.
However, we also observe a strong imbalance between the number of adult males (n=38) and females (n=20) buried at the site. If we only consider the 42 reproductive unions inferred from the offspring buried at the site, the shortage of females (9 versus 20 males) is also striking, which means that a substantial proportion of adult females are missing in the necropolis. This suggests that it was twice as likely for an adult male to be buried at the site, than for a female at Gurgy, even though these females were an integral part of the group at a certain point in time, as they had offspring with local partners. This preferential funerary bias needs to be considered independently from the signal of female exogamy that we observe, but leaves open questions with respect to why these mothers were not buried at the site, where they went and where and if they were buried.
The data from Gurgy also allowed us to look more closely at the subadult individuals, as many of which are buried in the necropolis (n=37). The ratio of males to females of 1.06:1 matches the expected natural ratio of 1.05:1 139 , meaning that the sex ratio of subadults had no preferential bias (Extended Data Fig. 7b). Looking at the age-at-death distribution, the vast majority of the subadults were younger than 15 years old (n=34), with most of the children younger than 8 years old (n=27) (Extended Data Fig. 2c). The difference in sex ratio between subadults and adults suggests that older daughters, from around at least the age of 15, and maybe slightly younger, had left to join a new group, in line with a female exogamic residential system. This observation leads us to explore whether the age at which females left the group was related to a social threshold and tested this hypothesis by using different lines of evidence. On the basis of the archaeological context at Gurgy, we observe a shift in the funerary practices of children who died at around 7-8 years of age, when the usual grave goods accompanying the younger children were no longer used (Extended data Fig. 5b). An additional shift happened at around 15-16 years of age-at-death when they were associated with the same grave goods as adults, which could reflect the age of initiation or the rite of passage, i.e. social threshold of accession to adulthood 108 . Sex-specific rites of passage at this age are well known, specifically related to the moment when specific social and gender roles are assigned and/or boys and girls are ritually separated 140 . This often involves differential access to sites and places and the introduction of tabooed or permitted foods, which could be detectable by stable isotopic analyses. However, carbon, nitrogen, sulphur isotope data highlight a significant dietary, sex-based difference in adults that could reflect a genderbiased access and/or differential treatment 36 . To explore this sex-based difference in subadults (Extended data Fig. 5c), we ran a cluster comparison using the Calinski-Harabasz Index and calculated the ratio of the sum of between-cluster dispersion and of inter-cluster dispersion for all clusters. The empirical p-value, calculated using a permutation test with all '0! 2!3! = 24,310 permutations of the possible cluster labels, is significant (p=0.01069), and remains significant when including the "undetermined" individuals, meaning the same difference can be observed in the diets of males and females during childhood (Supplementary table 24, Extended data Fig. 5c).

Female genetic diversity and potential provenance
On the basis of the patterns of a female exogamic residential system employed by the Gurgy group, we explored the genetic diversity and the potential origin/provenance(s) of these females to gain an understanding of the social rules that governed this community. Heatmaps constructed from pairwise outgroup-f3-statistics (n=16) and IBD sharing (n=12) (Supplementary Note 5, Extended Data Fig. 4) show very few connections between females. We detect three pairs of females who were related in the 3 rd or 4 th degree, while all other pairs are not genetically related, or too distantly to be detected, which corresponds to the expected background diversity of the population. The mitochondrial diversity in Gurgy reflects the mobility pattern (Supplementary Note 6), as the mothers of each generation contributed new mtDNA lineages and no mitochondrial haplogroup is transmitted further than one daughter/son generation, except for the female GLN325 who stayed in her lineage group and passed her mitochondrial haplogroup on to her offspring of the next generations. The analysis of runs of homozygosity (Supplementary Note 4, Extended Data Fig. 9c) also show an absence of inbreeding in the group. Only one individual, GLN282, has long ROH which correspond to him being the offspring of a 2 nd or 3 rd cousin relationship, but since his mother was not buried at Gurgy, or not successfully genotyped, we cannot position her precisely within Pedigree A. The overall level of background relatedness corresponds to a relatively medium-sized population, compared to the large size of LBK groups 64 and is consistent with the reconstructed pedigrees. Finally, the analysis of strontium (Sr) isotopes also shows that female partners, who are identified as exogenous in the pedigrees, had lower Sr values than their respective mates, a signal that is clearly visible and repeated in each subsequent generation (Supplementary Note 11), corroborating exogenous origin of the females in line with the genetic results. The independent lines of evidence suggest that the Gurgy community maintained a social system of female exogamy with a number of external groups, presumably bound to by reciprocal alliances, which may have been structured by a range of features, such as population size, access and exchanges of resources, network, or common linguistic and cultural affinities.

Patrilineal and patrilocal norms and exceptions
Assuming the existence of a female exogamic residential system with diverse origins of exogenous females as a baseline, we also observe a number of exceptions to this "norm" at different levels on the maternal line.
One exception to this main structure is the adult female GLN325, a descendant of the main lineage, whose partner, GLN275, is an individual who was genetically unrelated to the main lineage, and carried the only other Y-chromosome haplogroup of the site, H2m. GLN311, an adult male designated as "unlinked unrelated" in Figure 1a, also carried Ychromosome haplogroup H2m, and is 2 nd -degree related to GLN270B in the Pedigree A through the maternal side, but we are unable to characterize his exact relationship within the tree. The particular case of this second male lineage, with connections to different generations, but specifically via the adult female GLN325, implies a degree of flexibility to the norm as viewed from the two main pedigrees. The fact that the partner of female GLN325, a male from another lineage, was evidently integrated into the group and had offspring with a lineage female shows that he and/or his status was not seen to be in conflict with the dominant lineage for land access and/or other claims. This was possibly indirectly legitimized through the 2 nd degree relationship of GLN311 with GLN270B, which links both lineages early in the tree. This could in turn indicate that the group was small in comparison, and therefore welcoming, in some situations, to incomers who were not direct descendants of the main founder lineage, or that some other social arrangements were involved, e.g., rights of usufruct 141 which gave access to individuals to use the land and/or resources, but not to own or inherit them.
Another exception to the observed predominant form of social organisation, inferred from the Gurgy funerary community, can be found in Pedigree B, and concerns female individual GLN288 and her daughter GLN289B. As the parents of GLN288 are missing, we cannot determine whether GLN288 is linked to the pedigree through her mother or her father. If she was linked through her mother to the main lineage of Pedigree B, we cannot exclude that the mother is missing because she had left the group to join another group as hypothesized for most of the other females from Gurgy, while her daughter GLN288 later returned to the group, then considered as an 'exogenous' partner. If she was linked through her father to Pedigree B, the main lineage is continued by one more generation. Irrespective of the two possibilities, GLN288 and GLN325 represent adult daughters, who had adult offspring buried at the site, which gives both of these individuals a special status. By contrast, the daughters GLN289B, GLN212 and GLN213 from Pedigree A represent the only three adult daughters without offspring. If we were to apply a strictly patrilocal and female exogamic system, these three should also have left to another group, therefore their presence at the site is also part of the exceptions observed in this cemetery.
Finally, the individual GLN282 with an inbreeding signal, resulting from his/her parents being 2 nd or 3 rd cousins also shows an exception to the rule by allowing rather closely related individuals to reproduce (Supplementary Note 4). The number of exceptions to the norm leads us to suggest that the patrilineal and patrilocal system was not absolutely strict or dogmatic social norm, but was rather permeable, allowing for exceptions or variations to the main inferences, for reasons we cannot assess with confidence.
Interaction with the regional network and size of the population Results from the IBD sharing analysis also revealed additional connections beyond the reconstructed pedigrees, indicating links through female lines. Here, we observed several pairs of the pedigrees that appear to share more IBD than expected according to the reconstructed pedigrees, but without questioning its robustness (Supplementary Note 3, Fig.  2). This includes individuals within Pedigree A, but also between Pedigrees A and B. All detected links, although relatively distant, can only be explained through the female lines. A likely explanation is a scenario in which female descendants of the woman who had left the Gurgy community returned after a few generations to find a partner in Gurgy in return.
Alternatively, incoming female partners came from the same community and were maternally related. Both cases would imply that the network of reciprocal mobility within which these movements happened, was small to retain continuous connections (intentional or unintentional), but at the same time also sufficiently large to integrate entirely unrelated females. This observation is consistent with the results from ROH for the entire group, which show intermediate levels of background relatedness that correspond to a medium-sized metapopulation (Supplementary Note 4). Together, these findings lend support to the existence of a wider and more fluid exchange network of many, potentially smaller groups, a phenomenon which is called 'generalized exchange' in ethnographic studies 142 .

Monogamous pairing
The absence of half-sibling relationships in the group of Gurgy (Supplementary Note 2) is another aspect that is critical for the inference of social structure of prehistoric communities. This observed absence is striking as this would imply that polygamy was not a common practice in this community. It also rules out serial monogamy, i.e., a second or third partnership after the death of the first partner, at least based on the individuals buried at the site, which as a result lends support to exclusively monogamous pairings.

Inferences beyond the site
From an archaeological perspective, the site Gurgy stands in contrast to the regional context of contemporaneous monumental sites that are associated with the Cerny culture, and which were built for selected individuals 12 . The only monumental site from the Cerny area which has been genetically investigated to date, Fleury-sur-Orne in Normandy, shows a strong social selection of individuals buried in different monuments according to different patrilineal lineages 22 (Supplementary Note 1). Given the structural differences when compared to Gurgy, but also to STP sites from the Paris Basin, direct inferences cannot made.
One of the possible interpretations for the situation at Gurgy is that two different communities, with different funerary practices and attitudes towards social ranking, were coexisting within the same territory at the same time. This hypothesis would find support from a cultural point of view, as Gurgy does not show a clear attribution to the Cerny culture based on archaeological data, although the site is contemporaneous, and Cerny sites are located nearby. Gurgy burials indeed show multiple influences from different contemporaneous cultural groups, some local, such as alcove burials from LBK-derived groups in the West, with others originating further away, such as the Chamblandes cists from the Alps, or the presence of specific shell types from the Mediterranean area (Supplementary Note 1). These diverse cultural influences question the representativeness of Gurgy in the local Cerny context, but also of its social practices. However, the assumption that Gurgy was not fully culturally embedded in the surrounding context does not align with findings from the genetic data, which show strong links within a wider, but not completely random, biological network over several generations.
Given the absence of evidence that would point to a selection of individuals, i.e. an elite, on the basis of sex, age, economic or social hierarchies at the regional level, an alternative interpretation would be that the site represents the burial practices of the non-elite, that is of a broader stratum of a society in which the STP-buried individuals represent the elite at the regional level. Considering this hypothesis, and the fact that Gurgy was used by a single genetically related group, we would expect contemporaneous graveyards of similar sizes to meet the expectations from the observed genetic diversity estimates, such as mitochondrial haplogroup diversity and runs of homozygosity. However, only three other contemporaneous graveyards without monuments are known from the area, all of which are also much smaller: Monéteau 'Macherin' located only three kilometres away from Gurgy, Vignely 'La Porte aux Bergers', and Chichery 'sur les Pâtureaux' with 15, 17, and 27 buried individuals, respectively [16][17][18]20 (Supplementary Note 1). If we consider all of the individuals buried at these sites as potential non-elite people, the total number (n=187) is too low compared to the known 120 individuals buried in the monumental sites 12,13,20 , and would either suggest a substantial funerary bias (a higher chance of not being granted a burial) or an excavation bias (a higher chance of not observing regular inhumations, or finding them).
Looking at the site level, we can observe a slight emphasis on, if not at least a hierarchy of, some individuals. For example, the larger sizes of the graves of GLN270B's son (GLN237A) and grandson (GLN221B). However, these hints are far from the ostentatious demonstration visible in the STPs, and none of the elements that emphasize the hierarchical structure at STP sites, such as monuments, gender-related scenography, grave goods, are visible at Gurgy.
The translocation and secondary inhumation of individual GLN270B, the main ancestor of the large Pedigree A, points strongly to a specific funerary treatment compared to all other individuals buried at Gurgy, even though no other sign of power/wealth in the material culture was found. We speculate that it must have been important for his community/family to establish a connection to the ancestors and to (re)bury him as a founder in the very place where also his descendant will be buried for a few generations. However, this did not reach a level of supra-regional significance outside the Gurgy community, as no externally visible signs of representation were found.
At present, we lean towards the last hypothesis, which suggests that the different necropolises without monuments in the Paris Basin do represent the 'commoners', while many others, which we assume would have had a similar structure and/or organisation, have not been found yet. We argue that this scenario is more in line with the genetic data that shows evidence for wider and well-connected network over several generations. However, we acknowledge that the lack of comparative data from STP sites and non-monumental sites from the same region presents a current limitation to go beyond this tentative interpretation.

Supplementary Note 14.2. Demographic inferences
A group structure as described above is a perfect dataset to test paleodemographic hypotheses. Following the demographic approach proposed by P. Sellier (2011) 143 , we first tried to characterize the population sample under study. When we construct the mortality table from the ages at death of all the individuals in the necropolis (Supplementary table 19), we notice a deficit in infants/newborns ([0] year class) compared to an expected pattern of mortality in (pre-)history 144 , which is common for this period (Extended Data Fig. 6f). On one hand, when we look at the Pedigree A, the near absence of any young children is obvious in the first generations, as is the absence of adults in the last generations. It may seem reasonable to consider that some of the individuals definitely missing in generations 2 and 3 could be part of the individuals buried here, but for whom we have no genetic data. On the other hand, it is possible that for generation 2 and from generation 4 onwards the missing adults did not die on site.
Therefore, the structure of this population does not follow a natural mortality curve, or rather the composition of the buried group indicates a selection against natural mortality (Extended data Fig. 6f). The selection concerns the absence of children in the early stages, and then the absence of adults towards the end of the occupation phase. For the generations in between, an absence of adult women from the patrilocal lineage is noticeable, while the buried women come from other lineages, that are themselves rarely related to each other's.
In generations 2 and 3 of Pedigree A, we observe that four couples had four or five sons and two of these couples one or two more daughters, all of whom reached adulthood. As the majority of these children in generations 3 and 4 are men who died in adulthood, buried or not at the site, we would expect an equivalent number of women, as the ratio at birth between males and females is 1.05:1 139 . This suggests that each of these four couples must have had up to 10 or 12 children, and possibly more. Indeed, it can be considered that some of the individuals died at an early age, as expected from the mortality pattern commonly observed in prehistoric societies, but this cannot explain the absence of female individuals. Moreover, there are individuals in the necropolis who did not yield sufficient DNA data, and who are potentially these missing siblings.
There are therefore too many missing individuals to be able to construct new mortality tables by generation or according to other breakdowns, but, in spite of this, it seems interesting to suggest a possible range of numbers constituting the group using the Gurgy necropolis and the assumed living people simultaneously. To do this, we have to assume that all of the deceased individuals are present in this necropolis, which is false, as just stated. However, this a priori will allow us to make an a minima proposal. The equation proposed by Acsádi and Nemeskéri in 1970 145 could be used here: where P represents the population size, here the group who lived in a same place at the same time, D the total number of deaths, / / the life expectancy at birth, t the time of use of the final site, and k, which is a correction coefficient set at 10% of t.
An attempt to calculate life expectancy at birth is provided in the mortality table  (Supplementary table 19). These values must be taken with caution since at least the deceased subadults for generations 2 to 4 and most of the adults in generations 5 and 6 are missing. According to the estimates provided by the radiocarbon modelling, we can apply alternative estimates of the duration of site use.
• For a 120-year duration of use: P = 12+(128x33.1)/120 = 47 individuals. If we set a lower life expectancy at birth, which would seem to be expected given the deficit of infants, then the number of individuals would also be lower, around 110 for a 30year period of use and 59 for a 60-year period of use (214 for 15 years), and a life expectancy at birth of 25 years.
The estimate of a community of a few dozen people, ranging from 50 to nearly 200 is a credible range. The main drawback of this kind of approach is that any attempt to assess demographics on such data assumes a constant population 143 , which is far from being the case with female arrivals and departures in particular, even if one could propose that these exchanges might compensate for each other. As we have demonstrated, the Gurgy community started with a small group, which founded the site, and expanded after one or two generations. This chronological dynamic, possibly fluctuating over time, also needs to be taken into consideration when we estimate the size of this group.

Supplementary Note 14.3. Local mobility inferences from multiple lines of evidence
As already described (Supplementary Note 13), the site of Gurgy 'les Noisats', especially when considering the findings from Pedigree A, indicates that the individuals that were buried at the site came from another geographic location, settled in the area, and used the necropolis over several (2-3) generations (Supplementary Note 13), before leaving for another settlement. The Sr isotope data support this scenario with lower 87 Sr/ 86 Sr values for the first generations, as a signal of their exogenous origin (Supplementary Note 11), similar to that of exogenous females.
Strontium isotope data revealed regular variations between each generation (Fig. 3). Keeping in mind the potential gaps between the generations, and the fact that individuals of each generation are not necessarily synchronous, it nonetheless seems that each generation settled in an area different from the previous one. The range of these territories is unknown, as Sr values are sensitive to subtle differences in the substratum, and the size of these territories could range from a few hundred meters to several (tens of) kilometers. This 'intergenerational territorial mobility' (Supplementary Note 11) is highlighted for a Neolithic group for the first time and attests to a "short-term" exploitation of the environment.
Carbon, nitrogen, and sulphur data This "intergenerational territorial mobility", where each generation of individuals resides in a new location compared to the last, as depicted by Sr isotopes, is related to another important assessment: the variability of carbon, nitrogen, and sulphur (CNS) stable isotope ratios recorded in bones and teeth. Previous analyses of CNS stable isotope ratios in bone and dentine collagen have been performed on most of the individuals from Gurgy, highlighting age-, and sex-related variability 32,36 . Isotopic similarities were found to be linked to spatial proximity (groups of individuals buried in nearby graves shared more similar isotopic values, especially for N isotopes). The CNS isotopic variability recorded at the intra-and interindividual level can be due to the territorial variability between the generations or family groups. The importance of environmental variability in stable isotope data for Neolithic humans and animals has already been demonstrated by Goude and Fontugne 146 , but if an "intergenerational territorial mobility" is a common practice in agropastoral groups, the CNS isotopic ratios should be considered according to these new cultural and economic factors, rather than with a basic interpretative approach (involving age, sex, general biological/archaeological factors). The association of genetic information with CNS isotopic data reveals similarities between close family members. It is possible that individuals from a given family branch and close generations share similar diets, resources, and environments, demonstrating resource management strategies at the sub-lineage level. Therefore, the interpretation of isotopic data ( 87 Sr/ 86 Sr and CNS) and, in turn, of human behaviors, changes with the additional evidence of biological relatedness, generations and status (such as genetically exogenous or unrelated people).
Consequently, the isotopic data of the Gurgy funerary assemblage provide new information on the behavior of early European farmers. Isotopic data from other European Neolithic groups clearly show a high (seasonal, multi-annual, or at least regular during infancy and childhood) mobility of Neolithic and prehistoric farmers in general 36,147 . This mobility is likely essential in adapting to the environment and to surviving, even within a context of plant/animal domestication.

An alternative model of mobility during the Neolithic
Evidence of mobility is visible in the Gurgy dataset, at least from a genomic point of view. Specifically, we observed evidence of mobility among women who relocated between groups, whereas men remained in their group (Supplementary Note 14.1). This pattern is clear in Gurgy, and we suggest that such a model must be extended to a regional network level to make this pattern consistent and sustainable between groups. The group at Gurgy came from some other location to use this necropolis, stayed for a few decades, and left for somewhere else (Supplementary Note 12).
The additional information provided by the isotopic analyses ( 87 Sr/ 86 Sr and CNS) indicates another, more fine-grained level of mobility, on the basis of subtle evidence for a different environmental background for each generation. The alternative model suggests a move of each generation to another geographical location, potentially very close to the previous one, yet resulting in a slightly different isotope signature, while maintaining a common burial ground. The absence of settlements in the Gurgy area means that we cannot corroborate this hypothesis with archaeological data. The Gurgy necropolis is certainly central to the Gurgy community and represents the point of overlap for the two large pedigrees and associated kin, even though, as the isotopic data suggest, the people from Gurgy might not have lived consistently at the same place for each generation.
Seasonally changing residences, as reflected by the availability of natural resources, is a pattern that we are more used to observing in mobility studies of hunter-gatherers 148,149 . This study proposes a new outlook on the structure and organization of Neolithic subsistence, advocating a higher level of generational mobility (and/or fraction of the communities) than previously anticipated, but in a different mode than is known for hunter-gatherers.